| | | 1 - 1 - Why do we need machine learning [13 min].mp4 | 15.05 MB |
| | | 1 - 2 - What are neural networks [8 min].mp4 | 9.76 MB |
| | | 1 - 3 - Some simple models of neurons [8 min].mp4 | 9.26 MB |
| | | 1 - 4 - A simple example of learning [6 min].mp4 | 6.57 MB |
| | | 1 - 5 - Three types of learning [8 min].mp4 | 8.96 MB |
| | | 10 - 1 - Why it helps to combine models [13 min].mp4 | 15.12 MB |
| | | 10 - 2 - Mixtures of Experts [13 min].mp4 | 14.98 MB |
| | | 10 - 3 - The idea of full Bayesian learning [7 min].mp4 | 8.39 MB |
| | | 10 - 4 - Making full Bayesian learning practical [7 min].mp4 | 8.13 MB |
| | | 10 - 5 - Dropout [9 min].mp4 | 9.69 MB |
| | | 2 - 1 - Types of neural network architectures [7 min].mp4 | 8.78 MB |
| | | 2 - 2 - Perceptrons The first generation of neural networks [8 min].mp4 | 9.39 MB |
| | | 2 - 3 - A geometrical view of perceptrons [6 min].mp4 | 7.32 MB |
| | | 2 - 4 - Why the learning works [5 min].mp4 | 5.9 MB |
| | | 2 - 5 - What perceptrons cant do [15 min].mp4 | 16.57 MB |
| | | 3 - 1 - Learning the weights of a linear neuron [12 min].mp4 | 13.52 MB |
| | | 3 - 2 - The error surface for a linear neuron [5 min].mp4 | 5.89 MB |
| | | 3 - 3 - Learning the weights of a logistic output neuron [4 min].mp4 | 4.37 MB |
| | | 3 - 4 - The backpropagation algorithm [12 min].mp4 | 13.35 MB |
| | | 3 - 5 - Using the derivatives computed by backpropagation [10 min].mp4 | 11.15 MB |
| | | 4 - 1 - Learning to predict the next word [13 min].mp4 | 14.28 MB |
| | | 4 - 2 - A brief diversion into cognitive science [4 min].mp4 | 5.31 MB |
| | | 4 - 3 - Another diversion The softmax output function [7 min].mp4 | 8.03 MB |
| | | 4 - 4 - Neuro-probabilistic language models [8 min].mp4 | 8.93 MB |
| | | 4 - 5 - Ways to deal with the large number of possible outputs [15 min].mp4 | 14.26 MB |
| | | 5 - 1 - Why object recognition is difficult [5 min].mp4 | 5.37 MB |
| | | 5 - 2 - Achieving viewpoint invariance [6 min].mp4 | 6.89 MB |
| | | 5 - 3 - Convolutional nets for digit recognition [16 min].mp4 | 18.46 MB |
| | | 5 - 4 - Convolutional nets for object recognition [17min].mp4 | 23.03 MB |
| | | 6 - 1 - Overview of mini-batch gradient descent.mp4 | 9.6 MB |
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