Course 1 - Neural Network and Deep Learning
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- Last Updated: Thursday, 29 October 2020 18:24
- Published: Sunday, 30 August 2020 21:08
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Course 1: Neural Networks and Deep Learning.
This course introduces regression, then Neural networks. It has multiple python exercises, which should be completed. It has 4 sections:
1. Intro to Deep Learning: This is very level intro and nothing technical. Can be watched in fast mode
2. Neural Network basics: This is very important technical intro to NN. It has a example, which should be understood well. I had to repeat the lectures multiple times since there is so much material here. Most of your time in this course, should be spent on this section. You will learn a lot of new things: puthon, numpy, other python modules, regression terms, etc. So, go slow over this section. Things get easier from here on.
3. Shallow neural network: This has another example which is built using a 2 layer neural network. This example shows that 2 layer NN performs better than just plain regression.
4. Deep Neural Network: This section builds on top of 2 layer NN built above, and generalizes it to L layer NN.