Machine Learning in C (Episode 1) скачать в хорошем качестве

Machine Learning in C (Episode 1)

Chapters: 00:00:00 - Intro 00:01:21 - What is Machine Learning 00:03:03 - Mathematical Modeling 00:08:15 - Plan for Today 00:10:32 - Our First Model 00:12:24 - Training Data for the Model 00:17:05 - Initializing the Model 00:19:52 - Measuring How Well Model Works 00:27:56 - Improving the Cost Function 00:32:27 - Approximating Derivatives 00:41:25 - Training Process 00:45:59 - Artifician Neurons 00:50:11 - Adding Bias to the Model 00:56:16 - More Complex Model 00:58:41 - Simple Logic Gates Model 01:06:04 - Activation Function 01:15:24 - Troubleshooting the Model 01:25:04 - Adding Bias to the Gates Model 01:27:36 - Plotting the Cost Function 01:29:28 - Muxiphobia 01:31:43 - How I Understand Bias 01:33:20 - Other Logic Gates 01:36:13 - XOR-gate with 1 neuron 01:38:46 - XOR-gate with multiple neurons 01:49:14 - Coding XOR-gate model 01:57:53 - Human Brain VS Artificial Neural Network 02:00:26 - Continue coding XOR-gate model 02:15:14 - Non-XOR-gates with XOR Architecture 02:18:30 - Looking Inside of Neural Network 02:24:57 - Arbitrary Logic Circuits 02:27:23 - Shapes Classifier 02:29:42 - Better Representation of Neural Networks 02:30:36 - Outro 02:30:50 - Smooch References: https://github.com/tsoding/perceptron Notes: https://github.com/tsoding/ml-notes Support: BTC: bc1qj820dmeazpeq5pjn89mlh9lhws7ghs9v34x9v9