MIT 9.40 Introduction to Neural Computation, Spring 2018
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What you'll learn
This course includes
- 24.5 hours of video
- Certificate of completion
- Access on mobile and TV
Course content
1 modules • 20 lessons • 24.5 hours of video
MIT 9.40 Introduction to Neural Computation, Spring 2018
20 lessons
• 24.5 hours
MIT 9.40 Introduction to Neural Computation, Spring 2018
20 lessons
• 24.5 hours
- 1: Course Overview and Ionic Currents - Intro to Neural Computation 01:10:29
- 2: Resistor Capacitor Circuit and Nernst Potential - Intro to Neural Computation 01:19:40
- 3: Resistor Capacitor Neuron Model - Intro to Neural Computation 01:06:14
- 4: Hodgkin-Huxley Model Part 1 - Intro to Neural Computation 01:14:56
- 5: Hodgkin-Huxley Model Part 2 - Intro to Neural Computation 01:18:56
- 6: Dendrites - Intro to Neural Computation 01:06:30
- 7: Synapses - Intro to Neural Computation 01:18:10
- 8: Spike Trains - Intro to Neural Computation 56:46
- 9: Receptive Fields - Intro to Neural Computation 01:17:35
- 10: Time Series - Intro to Neural Computation 01:18:53
- 11: Spectral Analysis Part 1 - Intro to Neural Computation 01:17:38
- 12: Spectral Analysis Part 2 - Intro to Neural Computation 01:12:23
- 13: Spectral Analysis Part 3 - Intro to Neural Computation 01:08:32
- 14: Rate Models and Perceptrons - Intro to Neural Computation 01:15:25
- 15: Matrix Operations - Intro to Neural Computation 01:17:48
- 16: Basis Sets - Intro to Neural Computation 01:12:07
- 17: Principal Components Analysis_ - Intro to Neural Computation 01:21:19
- 18: Recurrent Networks - Intro to Neural Computation 01:19:13
- 19: Neural Integrators - Intro to Neural Computation 01:07:51
- 20: Hopfield Networks - Intro to Neural Computation 01:13:07
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