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14.15J Networks (MIT) 14.15J Networks (MIT)

Description

Networks are ubiquitous in our modern society. The World Wide Web that links us to and enables information flows with the rest of the world is the most visible example. It is, however, only one of many networks within which we are situated. Our social life is organized around networks of friends and colleagues. These networks determine our information, influence our opinions, and shape our political attitudes. They also link us, often through important but weak ties, to everybody else in the United States and in the world. Economic and financial markets also look much more like networks than anonymous marketplaces. Firms interact with the same suppliers and customers and use Web-like supply chains. Financial linkages, both among banks and between consumers, companies and banks, also form a Networks are ubiquitous in our modern society. The World Wide Web that links us to and enables information flows with the rest of the world is the most visible example. It is, however, only one of many networks within which we are situated. Our social life is organized around networks of friends and colleagues. These networks determine our information, influence our opinions, and shape our political attitudes. They also link us, often through important but weak ties, to everybody else in the United States and in the world. Economic and financial markets also look much more like networks than anonymous marketplaces. Firms interact with the same suppliers and customers and use Web-like supply chains. Financial linkages, both among banks and between consumers, companies and banks, also form a

Subjects

networks | networks | crowds | crowds | markets | markets | highly connected world | highly connected world | social networks | social networks | economic networks | economic networks | power networks | power networks | communication networks | communication networks | game theory | game theory | graph theory | graph theory | branching processes | branching processes | random graph models | random graph models | rich get richer phenomena | rich get richer phenomena | power laws | power laws | small worlds | small worlds | Erd?s-Renyi graphs | Erd?s-Renyi graphs | degree distributions | degree distributions | phase transitions | phase transitions | connectedness | connectedness | and giant component | and giant component | link analysis | link analysis | web search | web search | navigation | navigation | decentralized search | decentralized search | preferential attachment | preferential attachment | epidemics | epidemics | diffusion through networks | diffusion through networks | SIR | SIR | (susceptible | (susceptible | infected | infected | removed) | removed) | SIS | SIS | susceptible) | susceptible) | strategies | strategies | payoffs | payoffs | normal forms | normal forms | Nash equilibrium | Nash equilibrium | traffic networks | traffic networks | negative externalities | negative externalities | Braess' paradox | Braess' paradox | potential games | potential games | myopic behavior | myopic behavior | fictitious play | fictitious play | repeated games | repeated games | prisoner's dilemma | prisoner's dilemma | cooperation | cooperation | perfect information | perfect information | imperfect information | imperfect information | positive externalities | positive externalities | strategic complements | strategic complements | path dependence | path dependence | diffusion of innovation | diffusion of innovation | contagion pheonomena | contagion pheonomena | Bayes's rule | Bayes's rule | Bayesian Nash equilibrium | Bayesian Nash equilibrium | first price auctions | first price auctions | second price auctions | second price auctions | social learning | social learning | Bayesian learning | Bayesian learning | copying | copying | herding | herding | herd behavior | herd behavior | informational cascades | informational cascades | decisions | decisions | social choice | social choice | Condorcet jury theorem | Condorcet jury theorem | political economy | political economy

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htm

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Readme file for Introduction to Artificial Intelligence

Description

This readme file contains details of links to all the Introduction to Artificial Intelligence module's material held on Jorum and information about the module as well.

Subjects

ukoer | evolutionary algorithm lecture | algorithm tutorial | genetic algorithm lecture | genetic algorithm example | evolutionary computation tutorial | artificial intelligence lecture | artificial intelligence tutorial | random processes reading material | semantic web reading material | neural networks video | evolutionary computation test | artificial intelligence test | knowledge representation test | neural networks test | evolutionary algorithm | genetic computation | genetic programming | evolutionary computation | artificial intelligence | introduction to artificial intelligence | search | problem solving | revision | knowledge representation | semantic web | neural network | neural networks | artificial neural networks | swarm intelligence | collective intelligence | robot societies | genetic computation lecture | genetic programming lecture | evolutionary computation lecture | introduction to artificial intelligence lecture | evolutionary algorithm tutorial | genetic computation tutorial | genetic programming tutorial | introduction to artificial intelligence tutorial | evolutionary algorithm example | genetic computation example | genetic programming example | evolutionary computation example | artificial intelligence example | introduction to artificial intelligence example | search lecture | problem solving lecture | search tutorial | problem solving tutorial | search example | problem solving example | revision reading material | search reading material | artificial intelligence reading material | introduction to artificial intelligence reading material | revision lecture | knowledge representation lecture | semantic web lecture | knowledge representation practical | semantic web practical | artificial intelligence practical | introduction to artificial intelligence practical | knowledge representation reading material | knowledge representation notes | semantic web notes | artificial intelligence notes | introduction to artificial intelligence notes | neural network lecture | neural networks lecture | artificial neural networks lecture | neural network reading material | neural networks reading material | artificial neural networks reading material | neural network practical | neural networks practical | artificial neural networks practical | neural network viewing material | neural networks viewing material | artificial neural networks viewing material | artificial intelligence viewing material | introduction to artificial intelligence viewing material | swarm intelligence lecture | collective intelligence lecture | robot societies lecture | swarm intelligence tutorial | collective intelligence tutorial | robot societies tutorial | evolutionary algorithm test | genetic computation test | genetic programming test | introduction to artificial intelligence test | search test | problem solving test | semantic web test | neural network test | artificial neural networks test | g700 | ai | g700 lecture | ai lecture | g700 tutorial | ai tutorial | g700 example | ai example | g700 reading material | ai reading material | g700 practical | ai practical | g700 notes | ai notes | g700 viewing material | ai viewing material | g700 test | ai test | Computer science | I100

License

Attribution-Noncommercial-Share Alike 2.0 UK: England & Wales Attribution-Noncommercial-Share Alike 2.0 UK: England & Wales http://creativecommons.org/licenses/by-nc-sa/2.0/uk/ http://creativecommons.org/licenses/by-nc-sa/2.0/uk/

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14.15J Networks (MIT)

Description

Networks are ubiquitous in our modern society. The World Wide Web that links us to and enables information flows with the rest of the world is the most visible example. It is, however, only one of many networks within which we are situated. Our social life is organized around networks of friends and colleagues. These networks determine our information, influence our opinions, and shape our political attitudes. They also link us, often through important but weak ties, to everybody else in the United States and in the world. Economic and financial markets also look much more like networks than anonymous marketplaces. Firms interact with the same suppliers and customers and use Web-like supply chains. Financial linkages, both among banks and between consumers, companies and banks, also form a

Subjects

networks | crowds | markets | highly connected world | social networks | economic networks | power networks | communication networks | game theory | graph theory | branching processes | random graph models | rich get richer phenomena | power laws | small worlds | Erd?s-Renyi graphs | degree distributions | phase transitions | connectedness | and giant component | link analysis | web search | navigation | decentralized search | preferential attachment | epidemics | diffusion through networks | SIR | (susceptible | infected | removed) | SIS | susceptible) | strategies | payoffs | normal forms | Nash equilibrium | traffic networks | negative externalities | Braess' paradox | potential games | myopic behavior | fictitious play | repeated games | prisoner's dilemma | cooperation | perfect information | imperfect information | positive externalities | strategic complements | path dependence | diffusion of innovation | contagion pheonomena | Bayes's rule | Bayesian Nash equilibrium | first price auctions | second price auctions | social learning | Bayesian learning | copying | herding | herd behavior | informational cascades | decisions | social choice | Condorcet jury theorem | political economy

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see https://ocw.mit.edu/terms/index.htm

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IV (MIT) IV (MIT)

Description

Includes audio/video content: AV selected lectures, AV faculty introductions, AV special element video. The basic objective of Unified Engineering is to give a solid understanding of the fundamental disciplines of aerospace engineering, as well as their interrelationships and applications. These disciplines are Materials and Structures (M); Computers and Programming (C); Fluid Mechanics (F); Thermodynamics (T); Propulsion (P); and Signals and Systems (S). In choosing to teach these subjects in a unified manner, the instructors seek to explain the common intellectual threads in these disciplines, as well as their combined application to solve engineering Systems Problems (SP). Throughout the year, the instructors emphasize the connections among the disciplines. Includes audio/video content: AV selected lectures, AV faculty introductions, AV special element video. The basic objective of Unified Engineering is to give a solid understanding of the fundamental disciplines of aerospace engineering, as well as their interrelationships and applications. These disciplines are Materials and Structures (M); Computers and Programming (C); Fluid Mechanics (F); Thermodynamics (T); Propulsion (P); and Signals and Systems (S). In choosing to teach these subjects in a unified manner, the instructors seek to explain the common intellectual threads in these disciplines, as well as their combined application to solve engineering Systems Problems (SP). Throughout the year, the instructors emphasize the connections among the disciplines.

Subjects

Unified | Unified | Unified Engineering | Unified Engineering | aerospace | aerospace | CDIO | CDIO | C-D-I-O | C-D-I-O | conceive | conceive | design | design | implement | implement | operate | operate | team | team | team-based | team-based | discipline | discipline | materials | materials | structures | structures | materials and structures | materials and structures | computers | computers | programming | programming | computers and programming | computers and programming | fluids | fluids | fluid mechanics | fluid mechanics | thermodynamics | thermodynamics | propulsion | propulsion | signals | signals | systems | systems | signals and systems | signals and systems | systems problems | systems problems | fundamentals | fundamentals | technical communication | technical communication | graphical communication | graphical communication | communication | communication | reading | reading | research | research | experimentation | experimentation | personal response system | personal response system | prs | prs | active learning | active learning | First law | First law | first law of thermodynamics | first law of thermodynamics | thermo-mechanical | thermo-mechanical | energy | energy | energy conversion | energy conversion | aerospace power systems | aerospace power systems | propulsion systems | propulsion systems | aerospace propulsion systems | aerospace propulsion systems | heat | heat | work | work | thermal efficiency | thermal efficiency | forms of energy | forms of energy | energy exchange | energy exchange | processes | processes | heat engines | heat engines | engines | engines | steady-flow energy equation | steady-flow energy equation | energy flow | energy flow | flows | flows | path-dependence | path-dependence | path-independence | path-independence | reversibility | reversibility | irreversibility | irreversibility | state | state | thermodynamic state | thermodynamic state | performance | performance | ideal cycle | ideal cycle | simple heat engine | simple heat engine | cycles | cycles | thermal pressures | thermal pressures | temperatures | temperatures | linear static networks | linear static networks | loop method | loop method | node method | node method | linear dynamic networks | linear dynamic networks | classical methods | classical methods | state methods | state methods | state concepts | state concepts | dynamic systems | dynamic systems | resistive circuits | resistive circuits | sources | sources | voltages | voltages | currents | currents | Thevinin | Thevinin | Norton | Norton | initial value problems | initial value problems | RLC networks | RLC networks | characteristic values | characteristic values | characteristic vectors | characteristic vectors | transfer function | transfer function | ada | ada | ada programming | ada programming | programming language | programming language | software systems | software systems | programming style | programming style | computer architecture | computer architecture | program language evolution | program language evolution | classification | classification | numerical computation | numerical computation | number representation systems | number representation systems | assembly | assembly | SimpleSIM | SimpleSIM | RISC | RISC | CISC | CISC | operating systems | operating systems | single user | single user | multitasking | multitasking | multiprocessing | multiprocessing | domain-specific classification | domain-specific classification | recursive | recursive | execution time | execution time | fluid dynamics | fluid dynamics | physical properties of a fluid | physical properties of a fluid | fluid flow | fluid flow | mach | mach | reynolds | reynolds | conservation | conservation | conservation principles | conservation principles | conservation of mass | conservation of mass | conservation of momentum | conservation of momentum | conservation of energy | conservation of energy | continuity | continuity | inviscid | inviscid | steady flow | steady flow | simple bodies | simple bodies | airfoils | airfoils | wings | wings | channels | channels | aerodynamics | aerodynamics | forces | forces | moments | moments | equilibrium | equilibrium | freebody diagram | freebody diagram | free-body | free-body | free body | free body | planar force systems | planar force systems | equipollent systems | equipollent systems | equipollence | equipollence | support reactions | support reactions | reactions | reactions | static determinance | static determinance | determinate systems | determinate systems | truss analysis | truss analysis | trusses | trusses | method of joints | method of joints | method of sections | method of sections | statically indeterminate | statically indeterminate | three great principles | three great principles | 3 great principles | 3 great principles | indicial notation | indicial notation | rotation of coordinates | rotation of coordinates | coordinate rotation | coordinate rotation | stress | stress | extensional stress | extensional stress | shear stress | shear stress | notation | notation | plane stress | plane stress | stress equilbrium | stress equilbrium | stress transformation | stress transformation | mohr | mohr | mohr's circle | mohr's circle | principal stress | principal stress | principal stresses | principal stresses | extreme shear stress | extreme shear stress | strain | strain | extensional strain | extensional strain | shear strain | shear strain | strain-displacement | strain-displacement | compatibility | compatibility | strain transformation | strain transformation | transformation of strain | transformation of strain | mohr's circle for strain | mohr's circle for strain | principal strain | principal strain | extreme shear strain | extreme shear strain | uniaxial stress-strain | uniaxial stress-strain | material properties | material properties | classes of materials | classes of materials | bulk material properties | bulk material properties | origin of elastic properties | origin of elastic properties | structures of materials | structures of materials | atomic bonding | atomic bonding | packing of atoms | packing of atoms | atomic packing | atomic packing | crystals | crystals | crystal structures | crystal structures | polymers | polymers | estimate of moduli | estimate of moduli | moduli | moduli | composites | composites | composite materials | composite materials | modulus limited design | modulus limited design | material selection | material selection | materials selection | materials selection | measurement of elastic properties | measurement of elastic properties | stress-strain | stress-strain | stress-strain relations | stress-strain relations | anisotropy | anisotropy | orthotropy | orthotropy | measurements | measurements | engineering notation | engineering notation | Hooke | Hooke | Hooke's law | Hooke's law | general hooke's law | general hooke's law | equations of elasticity | equations of elasticity | boundary conditions | boundary conditions | multi-disciplinary | multi-disciplinary | models | models | engineering systems | engineering systems | experiments | experiments | investigations | investigations | experimental error | experimental error | design evaluation | design evaluation | evaluation | evaluation | trade studies | trade studies | effects of engineering | effects of engineering | social context | social context | engineering drawings | engineering drawings

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htm

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8.591J Systems Biology (MIT) 8.591J Systems Biology (MIT)

Description

This course introduces the mathematical modeling techniques needed to address key questions in modern biology. An overview of modeling techniques in molecular biology and genetics, cell biology and developmental biology is covered. Key experiments that validate mathematical models are also discussed, as well as molecular, cellular, and developmental systems biology, bacterial chemotaxis, genetic oscillators, control theory and genetic networks, and gradient sensing systems. Additional specific topics include: constructing and modeling of genetic networks, lambda phage as a genetic switch, synthetic genetic switches, circadian rhythms, reaction diffusion equations, local activation and global inhibition models, center finding networks, general pattern formation models, modeling cell-cell co This course introduces the mathematical modeling techniques needed to address key questions in modern biology. An overview of modeling techniques in molecular biology and genetics, cell biology and developmental biology is covered. Key experiments that validate mathematical models are also discussed, as well as molecular, cellular, and developmental systems biology, bacterial chemotaxis, genetic oscillators, control theory and genetic networks, and gradient sensing systems. Additional specific topics include: constructing and modeling of genetic networks, lambda phage as a genetic switch, synthetic genetic switches, circadian rhythms, reaction diffusion equations, local activation and global inhibition models, center finding networks, general pattern formation models, modeling cell-cell co

Subjects

molecular systems biology | molecular systems biology | constructing and modeling of genetic networks | constructing and modeling of genetic networks | control theory and genetic networks | control theory and genetic networks | ambda phage as a genetic switch | ambda phage as a genetic switch | synthetic genetic switches | synthetic genetic switches | bacterial chemotaxis | bacterial chemotaxis | genetic oscillators | genetic oscillators | circadian rhythms | circadian rhythms | cellular systems biology | cellular systems biology | reaction diffusion equations | reaction diffusion equations | local activation and global inhibition models | local activation and global inhibition models | gradient sensing systems | gradient sensing systems | center finding networks | center finding networks | developmental systems biology | developmental systems biology | general pattern formation models | general pattern formation models | modeling cell-cell communication | modeling cell-cell communication | quorum sensing | quorum sensing | models for Drosophilia development | models for Drosophilia development | 8.591 | 8.591 | 7.81 | 7.81

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htm

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IV (MIT) IV (MIT)

Description

The basic objective of Unified Engineering is to give a solid understanding of the fundamental disciplines of aerospace engineering, as well as their interrelationships and applications. These disciplines are Materials and Structures (M); Computers and Programming (C); Fluid Mechanics (F); Thermodynamics (T); Propulsion (P); and Signals and Systems (S). In choosing to teach these subjects in a unified manner, the instructors seek to explain the common intellectual threads in these disciplines, as well as their combined application to solve engineering Systems Problems (SP). Throughout the year, the instructors emphasize the connections among the disciplines.Technical RequirementsMicrosoft® Excel software is recommended for viewing the .xls files The basic objective of Unified Engineering is to give a solid understanding of the fundamental disciplines of aerospace engineering, as well as their interrelationships and applications. These disciplines are Materials and Structures (M); Computers and Programming (C); Fluid Mechanics (F); Thermodynamics (T); Propulsion (P); and Signals and Systems (S). In choosing to teach these subjects in a unified manner, the instructors seek to explain the common intellectual threads in these disciplines, as well as their combined application to solve engineering Systems Problems (SP). Throughout the year, the instructors emphasize the connections among the disciplines.Technical RequirementsMicrosoft® Excel software is recommended for viewing the .xls files

Subjects

Unified | Unified | Unified Engineering | Unified Engineering | aerospace | aerospace | CDIO | CDIO | C-D-I-O | C-D-I-O | conceive | conceive | design | design | implement | implement | operate | operate | team | team | team-based | team-based | discipline | discipline | materials | materials | structures | structures | materials and structures | materials and structures | computers | computers | programming | programming | computers and programming | computers and programming | fluids | fluids | fluid mechanics | fluid mechanics | thermodynamics | thermodynamics | propulsion | propulsion | signals | signals | systems | systems | signals and systems | signals and systems | systems problems | systems problems | fundamentals | fundamentals | technical communication | technical communication | graphical communication | graphical communication | communication | communication | reading | reading | research | research | experimentation | experimentation | personal response system | personal response system | prs | prs | active learning | active learning | First law | First law | first law of thermodynamics | first law of thermodynamics | thermo-mechanical | thermo-mechanical | energy | energy | energy conversion | energy conversion | aerospace power systems | aerospace power systems | propulsion systems | propulsion systems | aerospace propulsion systems | aerospace propulsion systems | heat | heat | work | work | thermal efficiency | thermal efficiency | forms of energy | forms of energy | energy exchange | energy exchange | processes | processes | heat engines | heat engines | engines | engines | steady-flow energy equation | steady-flow energy equation | energy flow | energy flow | flows | flows | path-dependence | path-dependence | path-independence | path-independence | reversibility | reversibility | irreversibility | irreversibility | state | state | thermodynamic state | thermodynamic state | performance | performance | ideal cycle | ideal cycle | simple heat engine | simple heat engine | cycles | cycles | thermal pressures | thermal pressures | temperatures | temperatures | linear static networks | linear static networks | loop method | loop method | node method | node method | linear dynamic networks | linear dynamic networks | classical methods | classical methods | state methods | state methods | state concepts | state concepts | dynamic systems | dynamic systems | resistive circuits | resistive circuits | sources | sources | voltages | voltages | currents | currents | Thevinin | Thevinin | Norton | Norton | initial value problems | initial value problems | RLC networks | RLC networks | characteristic values | characteristic values | characteristic vectors | characteristic vectors | transfer function | transfer function | ada | ada | ada programming | ada programming | programming language | programming language | software systems | software systems | programming style | programming style | computer architecture | computer architecture | program language evolution | program language evolution | classification | classification | numerical computation | numerical computation | number representation systems | number representation systems | assembly | assembly | SimpleSIM | SimpleSIM | RISC | RISC | CISC | CISC | operating systems | operating systems | single user | single user | multitasking | multitasking | multiprocessing | multiprocessing | domain-specific classification | domain-specific classification | recursive | recursive | execution time | execution time | fluid dynamics | fluid dynamics | physical properties of a fluid | physical properties of a fluid | fluid flow | fluid flow | mach | mach | reynolds | reynolds | conservation | conservation | conservation principles | conservation principles | conservation of mass | conservation of mass | conservation of momentum | conservation of momentum | conservation of energy | conservation of energy | continuity | continuity | inviscid | inviscid | steady flow | steady flow | simple bodies | simple bodies | airfoils | airfoils | wings | wings | channels | channels | aerodynamics | aerodynamics | forces | forces | moments | moments | equilibrium | equilibrium | freebody diagram | freebody diagram | free-body | free-body | free body | free body | planar force systems | planar force systems | equipollent systems | equipollent systems | equipollence | equipollence | support reactions | support reactions | reactions | reactions | static determinance | static determinance | determinate systems | determinate systems | truss analysis | truss analysis | trusses | trusses | method of joints | method of joints | method of sections | method of sections | statically indeterminate | statically indeterminate | three great principles | three great principles | 3 great principles | 3 great principles | indicial notation | indicial notation | rotation of coordinates | rotation of coordinates | coordinate rotation | coordinate rotation | stress | stress | extensional stress | extensional stress | shear stress | shear stress | notation | notation | plane stress | plane stress | stress equilbrium | stress equilbrium | stress transformation | stress transformation | mohr | mohr | mohr's circle | mohr's circle | principal stress | principal stress | principal stresses | principal stresses | extreme shear stress | extreme shear stress | strain | strain | extensional strain | extensional strain | shear strain | shear strain | strain-displacement | strain-displacement | compatibility | compatibility | strain transformation | strain transformation | transformation of strain | transformation of strain | mohr's circle for strain | mohr's circle for strain | principal strain | principal strain | extreme shear strain | extreme shear strain | uniaxial stress-strain | uniaxial stress-strain | material properties | material properties | classes of materials | classes of materials | bulk material properties | bulk material properties | origin of elastic properties | origin of elastic properties | structures of materials | structures of materials | atomic bonding | atomic bonding | packing of atoms | packing of atoms | atomic packing | atomic packing | crystals | crystals | crystal structures | crystal structures | polymers | polymers | estimate of moduli | estimate of moduli | moduli | moduli | composites | composites | composite materials | composite materials | modulus limited design | modulus limited design | material selection | material selection | materials selection | materials selection | measurement of elastic properties | measurement of elastic properties | stress-strain | stress-strain | stress-strain relations | stress-strain relations | anisotropy | anisotropy | orthotropy | orthotropy | measurements | measurements | engineering notation | engineering notation | Hooke | Hooke | Hooke's law | Hooke's law | general hooke's law | general hooke's law | equations of elasticity | equations of elasticity | boundary conditions | boundary conditions | multi-disciplinary | multi-disciplinary | models | models | engineering systems | engineering systems | experiments | experiments | investigations | investigations | experimental error | experimental error | design evaluation | design evaluation | evaluation | evaluation | trade studies | trade studies | effects of engineering | effects of engineering | social context | social context | engineering drawings | engineering drawings | 16.01 | 16.01 | 16.02 | 16.02 | 16.03 | 16.03 | 16.04 | 16.04

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htm

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6.896 Theory of Parallel Hardware (SMA 5511) (MIT) 6.896 Theory of Parallel Hardware (SMA 5511) (MIT)

Description

6.896 covers mathematical foundations of parallel hardware, from computer arithmetic to physical design, focusing on algorithmic underpinnings. Topics covered include: arithmetic circuits, parallel prefix, systolic arrays, retiming, clocking methodologies, boolean logic, sorting networks, interconnection networks, hypercubic networks, P-completeness, VLSI layout theory, reconfigurable wiring, fat-trees, and area-time complexity. This course was also taught as part of the Singapore-MIT Alliance (SMA) programme as course number SMA 5511 (Theory of Parallel Hardware). 6.896 covers mathematical foundations of parallel hardware, from computer arithmetic to physical design, focusing on algorithmic underpinnings. Topics covered include: arithmetic circuits, parallel prefix, systolic arrays, retiming, clocking methodologies, boolean logic, sorting networks, interconnection networks, hypercubic networks, P-completeness, VLSI layout theory, reconfigurable wiring, fat-trees, and area-time complexity. This course was also taught as part of the Singapore-MIT Alliance (SMA) programme as course number SMA 5511 (Theory of Parallel Hardware).

Subjects

parallel hardware | parallel hardware | computer arithmetic | computer arithmetic | physical design | physical design | algorithms | algorithms | arithmetic circuits | arithmetic circuits | parallel prefix | parallel prefix | systolic arrays | systolic arrays | retiming | retiming | clocking methodologies | clocking methodologies | boolean logic | boolean logic | sorting networks | sorting networks | interconnection networks | interconnection networks | hypercubic networks | hypercubic networks | P-completeness | P-completeness | VLSI layout theory | VLSI layout theory | reconfigurable wiring | reconfigurable wiring | fat-trees | fat-trees | area-time complexity | area-time complexity

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htm

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15.564 Information Technology I (MIT) 15.564 Information Technology I (MIT)

Description

Information Technology I helps students understand technical concepts underlying current and future developments in information technology. There will be a special emphasis on networks and distributed computing. Students will also gain some hands-on exposure to powerful, high-level tools for making computers do amazing things, without the need for conventional programming languages. Since 15.564 is an introductory course, no knowledge of how computers work or are programmed is assumed. Information Technology I helps students understand technical concepts underlying current and future developments in information technology. There will be a special emphasis on networks and distributed computing. Students will also gain some hands-on exposure to powerful, high-level tools for making computers do amazing things, without the need for conventional programming languages. Since 15.564 is an introductory course, no knowledge of how computers work or are programmed is assumed.

Subjects

developing-country governments; international | developing-country governments; international | computers; future developments; networks;distributed computing; programming languages;firewall;e-business;computerarchitecture;operating systems;software development;database;user interface;telecommunication;data transmission;localarea network;wireless network;internet;world wide web;digital security | computers; future developments; networks;distributed computing; programming languages;firewall;e-business;computerarchitecture;operating systems;software development;database;user interface;telecommunication;data transmission;localarea network;wireless network;internet;world wide web;digital security | computers;future developments;networks;distributed computing;programming languages;firewall;e-business;computerarchitecture;operating systems;software development;database;user interface;telecommunication;data transmission;localarea network;wireless network;internet;world wide web;digital security | computers;future developments;networks;distributed computing;programming languages;firewall;e-business;computerarchitecture;operating systems;software development;database;user interface;telecommunication;data transmission;localarea network;wireless network;internet;world wide web;digital security | computers | computers | future developments | future developments | networks | networks | distributed computing | distributed computing | programming languages | programming languages | firewall | firewall | e-business | e-business | computer architecture | computer architecture | operating | operating | software development | software development | database | database | user interface | user interface | telecommunication | telecommunication | data transmission | data transmission | local area network | local area network | wireless network | wireless network | internet | internet | world wide web | world wide web | digital security | digital security | architecture | architecture | data | data | transmission | transmission | wireless | wireless | interface | interface | user | user | software | software | development | development | programming | programming | languages | languages | distributed | distributed | computing | computing | LAN | LAN | local | local | area | area | future | future | digital | digital | security | security | technology | technology | information | information | management | management | systems | systems | relational | relational | graphical | graphical | interfaces | interfaces | client/server | client/server | enterprise | enterprise | applications | applications | cryptography | cryptography | services | services | Microsoft | Microsoft | Access | Access | Lotus Notes | Lotus Notes | processing | processing | memory | memory | I/O | I/O | CPU | CPU | OS | OS | hardware | hardware | compression | compression | SQL | SQL | queries | queries | design | design | WAN | WAN | wide | wide | Ethernet | Ethernet | packet-switched | packet-switched | peer-to-peer | peer-to-peer | WWW | WWW | public | public | key | key | mining | mining | warehousing | warehousing | concepts | concepts | conceptual | conceptual | modern computing | modern computing | information management | information management | operating systems | operating systems | relational database systems | relational database systems | graphical user interfaces | graphical user interfaces | client/server systems | client/server systems | enterprise applications | enterprise applications | web.internet services | web.internet services | Microsoft Access | Microsoft Access | database management systems | database management systems | information technology | information technology | telecommunications | telecommunications | eBusiness applications | eBusiness applications | client | client | servers | servers | wireless area network | wireless area network

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MAS.961 Networks, Complexity and Its Applications (MIT) MAS.961 Networks, Complexity and Its Applications (MIT)

Description

Networks are a ubiquitous way to represent complex systems, including those in the social and economic sciences. The goal of the course is to equip students with conceptual tools that can help them understand complex systems that emerge in both nature and social systems. This is a course intended for a general audience and will discuss applications of networks and complexity to diverse systems, including epidemic spreading, social networks and the evolution of economic development. Networks are a ubiquitous way to represent complex systems, including those in the social and economic sciences. The goal of the course is to equip students with conceptual tools that can help them understand complex systems that emerge in both nature and social systems. This is a course intended for a general audience and will discuss applications of networks and complexity to diverse systems, including epidemic spreading, social networks and the evolution of economic development.

Subjects

social networks | social networks | complex networks | complex networks | macroconnections | macroconnections | Watts and Strogatz Model | Watts and Strogatz Model | Barabási-Albert Model | Barabási-Albert Model | Modularity and Community Structure | Modularity and Community Structure | The Lorenz Attractor | The Lorenz Attractor | Lyapunov Exponents | Lyapunov Exponents | visualizing networks | visualizing networks | network structure | network structure

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htm

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Introduction to Artificial Intelligence - Neural Networks

Description

This viewing material forms part of the "Neural Networks" topic in the Introduction to Artificial Intelligence module.

Subjects

ukoer | neural networks video | neural network | neural networks | artificial neural networks | artificial intelligence | introduction to artificial intelligence | neural network viewing material | neural networks viewing material | artificial neural networks viewing material | artificial intelligence viewing material | introduction to artificial intelligence viewing material | g700 | ai | g700 viewing material | ai viewing material | Computer science | I100

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7.349 Biological Computing: At the Crossroads of Engineering and Science (MIT) 7.349 Biological Computing: At the Crossroads of Engineering and Science (MIT)

Description

Imagine you are a salesman needing to visit 100 cities connected by a set of roads. Can you do it while stopping in each city only once? Even a supercomputer working at 1 trillion operations per second would take longer than the age of the universe to find a solution when considering each possibility in turn. In 1994, Leonard Adleman published a paper in which he described a solution, using the tools of molecular biology, for a smaller 7-city example of this problem. His paper generated enormous scientific and public interest, and kick-started the field of Biological Computing, the main subject of this discussion based seminar course. Students will analyze the Adleman paper, and the papers that preceded and followed it, with an eye for identifying the engineering and scientific aspects of Imagine you are a salesman needing to visit 100 cities connected by a set of roads. Can you do it while stopping in each city only once? Even a supercomputer working at 1 trillion operations per second would take longer than the age of the universe to find a solution when considering each possibility in turn. In 1994, Leonard Adleman published a paper in which he described a solution, using the tools of molecular biology, for a smaller 7-city example of this problem. His paper generated enormous scientific and public interest, and kick-started the field of Biological Computing, the main subject of this discussion based seminar course. Students will analyze the Adleman paper, and the papers that preceded and followed it, with an eye for identifying the engineering and scientific aspects of

Subjects

biological computing | biological computing | Leonard Adleman | Leonard Adleman | exquisite detection | exquisite detection | whole-cell computing | whole-cell computing | computation | computation | molecular biology | molecular biology | biotin-avidin | biotin-avidin | magnetic beads | magnetic beads | cellular processes | cellular processes | combinatorial problems | combinatorial problems | self-assembly | self-assembly | nanodevices | nanodevices | molecular machines | molecular machines | quorum sensing | quorum sensing | molecular switches | molecular switches | ciliates | ciliates | molecular gates | molecular gates | molecular circuits | molecular circuits | genetic switch | genetic switch | cellular networks | cellular networks | genetic networks | genetic networks | genetic circuits | genetic circuits

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htm

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8.592J Statistical Physics in Biology (MIT) 8.592J Statistical Physics in Biology (MIT)

Description

Statistical Physics in Biology is a survey of problems at the interface of statistical physics and modern biology. Topics include: bioinformatic methods for extracting information content of DNA; gene finding, sequence comparison, and phylogenetic trees; physical interactions responsible for structure of biopolymers; DNA double helix, secondary structure of RNA, and elements of protein folding; considerations of force, motion, and packaging; protein motors, membranes. We also look at collective behavior of biological elements, cellular networks, neural networks, and evolution. Statistical Physics in Biology is a survey of problems at the interface of statistical physics and modern biology. Topics include: bioinformatic methods for extracting information content of DNA; gene finding, sequence comparison, and phylogenetic trees; physical interactions responsible for structure of biopolymers; DNA double helix, secondary structure of RNA, and elements of protein folding; considerations of force, motion, and packaging; protein motors, membranes. We also look at collective behavior of biological elements, cellular networks, neural networks, and evolution.

Subjects

Bioinformatics | Bioinformatics | DNA | DNA | gene finding | gene finding | sequence comparison | sequence comparison | phylogenetic trees | phylogenetic trees | biopolymers | biopolymers | DNA double helix | DNA double helix | secondary structure of RNA | secondary structure of RNA | protein folding | protein folding | protein motors | protein motors | membranes | membranes | cellular networks | cellular networks | neural networks | neural networks | evolution | evolution

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htm

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Introduction to Artificial Intelligence - Neural Networks

Description

This lecture forms part of the "Neural Networks" topic in the Introduction to Artificial Intelligence module.

Subjects

ukoer | neural network | neural networks | artificial neural networks | artificial intelligence | introduction to artificial intelligence | neural network lecture | neural networks lecture | artificial neural networks lecture | artificial intelligence lecture | introduction to artificial intelligence lecture | g700 | ai | g700 lecture | ai lecture | Computer science | I100

License

Attribution-Noncommercial-Share Alike 2.0 UK: England & Wales Attribution-Noncommercial-Share Alike 2.0 UK: England & Wales http://creativecommons.org/licenses/by-nc-sa/2.0/uk/ http://creativecommons.org/licenses/by-nc-sa/2.0/uk/

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8.591J Systems Biology (MIT) 8.591J Systems Biology (MIT)

Description

Includes audio/video content: AV lectures. This course provides an introduction to cellular and population-level systems biology with an emphasis on synthetic biology, modeling of genetic networks, cell-cell interactions, and evolutionary dynamics. Cellular systems include genetic switches and oscillators, network motifs, genetic network evolution, and cellular decision-making. Population-level systems include models of pattern formation, cell-cell communication, and evolutionary systems biology. Includes audio/video content: AV lectures. This course provides an introduction to cellular and population-level systems biology with an emphasis on synthetic biology, modeling of genetic networks, cell-cell interactions, and evolutionary dynamics. Cellular systems include genetic switches and oscillators, network motifs, genetic network evolution, and cellular decision-making. Population-level systems include models of pattern formation, cell-cell communication, and evolutionary systems biology.

Subjects

molecular systems biology | molecular systems biology | genetic networks | genetic networks | control theory | control theory | synthetic genetic switches | synthetic genetic switches | bacterial chemotaxis | bacterial chemotaxis | genetic oscillators | genetic oscillators | circadian rhythms | circadian rhythms | cellular systems biology | cellular systems biology | reaction diffusion equations | reaction diffusion equations | local activation | local activation | global inhibition models | global inhibition models | gradient sensing systems | gradient sensing systems | center finding networks | center finding networks | general pattern formation models | general pattern formation models | cell-cell communication | cell-cell communication | quorum sensing | quorum sensing

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htm

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Introduction to Artificial Intelligence - Neural Networks

Description

This lecture forms part of the "Neural Networks" topic in the Introduction to Artificial Intelligence module.

Subjects

ukoer | neural network | neural networks | artificial neural networks | artificial intelligence | introduction to artificial intelligence | neural network lecture | neural networks lecture | artificial neural networks lecture | artificial intelligence lecture | introduction to artificial intelligence lecture | g700 | ai | g700 lecture | ai lecture | Computer science | I100

License

Attribution-Noncommercial-Share Alike 2.0 UK: England & Wales Attribution-Noncommercial-Share Alike 2.0 UK: England & Wales http://creativecommons.org/licenses/by-nc-sa/2.0/uk/ http://creativecommons.org/licenses/by-nc-sa/2.0/uk/

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Introduction to Artificial Intelligence - Neural Networks

Description

This lecture forms part of the "Neural Networks" topic in the Introduction to Artificial Intelligence module.

Subjects

ukoer | neural network | neural networks | artificial neural networks | artificial intelligence | introduction to artificial intelligence | neural network lecture | neural networks lecture | artificial neural networks lecture | artificial intelligence lecture | introduction to artificial intelligence lecture | g700 | ai | g700 lecture | ai lecture | Computer science | I100

License

Attribution-Noncommercial-Share Alike 2.0 UK: England & Wales Attribution-Noncommercial-Share Alike 2.0 UK: England & Wales http://creativecommons.org/licenses/by-nc-sa/2.0/uk/ http://creativecommons.org/licenses/by-nc-sa/2.0/uk/

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Introduction to Artificial Intelligence - Neural Networks

Description

This lecture forms part of the "Neural Networks" topic in the Introduction to Artificial Intelligence module.

Subjects

ukoer | neural network | neural networks | artificial neural networks | artificial intelligence | introduction to artificial intelligence | neural network lecture | neural networks lecture | artificial neural networks lecture | artificial intelligence lecture | introduction to artificial intelligence lecture | g700 | ai | g700 lecture | ai lecture | Computer science | I100

License

Attribution-Noncommercial-Share Alike 2.0 UK: England & Wales Attribution-Noncommercial-Share Alike 2.0 UK: England & Wales http://creativecommons.org/licenses/by-nc-sa/2.0/uk/ http://creativecommons.org/licenses/by-nc-sa/2.0/uk/

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6.002 Circuits and Electronics (MIT) 6.002 Circuits and Electronics (MIT)

Description

6.002 is designed to serve as a first course in an undergraduate electrical engineering (EE), or electrical engineering and computer science (EECS) curriculum. At MIT, 6.002 is in the core of department subjects required for all undergraduates in EECS. The course introduces the fundamentals of the lumped circuit abstraction. Topics covered include: resistive elements and networks; independent and dependent sources; switches and MOS transistors; digital abstraction; amplifiers; energy storage elements; dynamics of first- and second-order networks; design in the time and frequency domains; and analog and digital circuits and applications. Design and lab exercises are also significant components of the course. 6.002 is worth 4 Engineering Design Points. The 6.002 content was created collabora 6.002 is designed to serve as a first course in an undergraduate electrical engineering (EE), or electrical engineering and computer science (EECS) curriculum. At MIT, 6.002 is in the core of department subjects required for all undergraduates in EECS. The course introduces the fundamentals of the lumped circuit abstraction. Topics covered include: resistive elements and networks; independent and dependent sources; switches and MOS transistors; digital abstraction; amplifiers; energy storage elements; dynamics of first- and second-order networks; design in the time and frequency domains; and analog and digital circuits and applications. Design and lab exercises are also significant components of the course. 6.002 is worth 4 Engineering Design Points. The 6.002 content was created collabora

Subjects

Fundamentals of the lumped circuit abstraction | Fundamentals of the lumped circuit abstraction | Resistive elements and networks | Resistive elements and networks | independent and dependent sources | independent and dependent sources | switches and MOS devices | switches and MOS devices | digital abstraction | digital abstraction | amplifiers | amplifiers | and energy storage elements | and energy storage elements | Dynamics of first- and second-order networks | Dynamics of first- and second-order networks | design in the time and frequency domains | design in the time and frequency domains | analog and digital circuits and applications | analog and digital circuits and applications

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htm

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Introduction to Artificial Intelligence - Neural Networks

Description

This reading material forms part of the "Neural Networks" topic in the Introduction to Artificial Intelligence module.

Subjects

ukoer | neural network | neural networks | artificial neural networks | artificial intelligence | introduction to artificial intelligence | neural network reading material | neural networks reading material | artificial neural networks reading material | artificial intelligence reading material | introduction to artificial intelligence reading material | g700 | ai | g700 reading material | ai reading material | Computer science | I100

License

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Introduction to Artificial Intelligence - Neural Networks

Description

This reading material forms part of the "Neural Networks" topic in the Introduction to Artificial Intelligence module.

Subjects

ukoer | neural network | neural networks | artificial neural networks | artificial intelligence | introduction to artificial intelligence | neural network reading material | neural networks reading material | artificial neural networks reading material | artificial intelligence reading material | introduction to artificial intelligence reading material | g700 | ai | g700 reading material | ai reading material | Computer science | I100

License

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8.592J Statistical Physics in Biology (MIT) 8.592J Statistical Physics in Biology (MIT)

Description

Statistical Physics in Biology is a survey of problems at the interface of statistical physics and modern biology. Topics include: bioinformatic methods for extracting information content of DNA; gene finding, sequence comparison, and phylogenetic trees; physical interactions responsible for structure of biopolymers; DNA double helix, secondary structure of RNA, and elements of protein folding; considerations of force, motion, and packaging; protein motors, membranes. We also look at collective behavior of biological elements, cellular networks, neural networks, and evolution. Statistical Physics in Biology is a survey of problems at the interface of statistical physics and modern biology. Topics include: bioinformatic methods for extracting information content of DNA; gene finding, sequence comparison, and phylogenetic trees; physical interactions responsible for structure of biopolymers; DNA double helix, secondary structure of RNA, and elements of protein folding; considerations of force, motion, and packaging; protein motors, membranes. We also look at collective behavior of biological elements, cellular networks, neural networks, and evolution.

Subjects

8.592 | 8.592 | HST.452 | HST.452 | Statistical physics | Statistical physics | Bioinformatics | Bioinformatics | DNA | DNA | gene finding | gene finding | sequence comparison | sequence comparison | phylogenetic trees | phylogenetic trees | biopolymers | biopolymers | DNA double helix | DNA double helix | secondary structure of RNA | secondary structure of RNA | protein folding | protein folding | protein motors | protein motors | membranes | membranes | cellular networks | cellular networks | neural networks | neural networks | evolution | evolution

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htm

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Introduction to Artificial Intelligence - Neural Networks

Description

This reading material forms part of the "Neural Networks" topic in the Introduction to Artificial Intelligence module.

Subjects

ukoer | neural network | neural networks | artificial neural networks | artificial intelligence | introduction to artificial intelligence | neural network reading material | neural networks reading material | artificial neural networks reading material | artificial intelligence reading material | introduction to artificial intelligence reading material | g700 | ai | g700 reading material | ai reading material | Computer science | I100

License

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Introduction to Artificial Intelligence - Neural Networks

Description

This reading material forms part of the "Neural Networks" topic in the Introduction to Artificial Intelligence module

Subjects

ukoer | neural network | neural networks | artificial neural networks | artificial intelligence | introduction to artificial intelligence | neural network reading material | neural networks reading material | artificial neural networks reading material | artificial intelligence reading material | introduction to artificial intelligence reading material | g700 | ai | g700 reading material | ai reading material | Computer science | I100

License

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Introduction to Artificial Intelligence - Neural Networks

Description

This reading material forms part of the "Neural Networks" topic in the Introduction to Artificial Intelligence module.

Subjects

ukoer | neural network | neural networks | artificial neural networks | artificial intelligence | introduction to artificial intelligence | neural network reading material | neural networks reading material | artificial neural networks reading material | artificial intelligence reading material | introduction to artificial intelligence reading material | g700 | ai | g700 reading material | ai reading material | Computer science | I100

License

Attribution-Noncommercial-Share Alike 2.0 UK: England & Wales Attribution-Noncommercial-Share Alike 2.0 UK: England & Wales http://creativecommons.org/licenses/by-nc-sa/2.0/uk/ http://creativecommons.org/licenses/by-nc-sa/2.0/uk/

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Introduction to Artificial Intelligence - Neural Networks

Description

This reading material forms part of the "Neural Networks" topic in the Introduction to Artificial Intelligence module.

Subjects

ukoer | neural network | neural networks | artificial neural networks | artificial intelligence | introduction to artificial intelligence | neural network reading material | neural networks reading material | artificial neural networks reading material | artificial intelligence reading material | introduction to artificial intelligence reading material | g700 | ai | g700 reading material | ai reading material | Computer science | I100

License

Attribution-Noncommercial-Share Alike 2.0 UK: England & Wales Attribution-Noncommercial-Share Alike 2.0 UK: England & Wales http://creativecommons.org/licenses/by-nc-sa/2.0/uk/ http://creativecommons.org/licenses/by-nc-sa/2.0/uk/

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