6.1 API design for complete beginners | End to End Machine Learning

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314. Neural Network Optimization

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Cottonwood Code Map

1. Single Hyperparameter Optimization

1.1 What is hyperparameter optimization? (3:50)
1.2 Code for testing repeatability (4:24)
1.3 Repeatability results (5:33)
1.4 Optimize a single hyperparameter (14:05)

2. Multi-Hyperparameter Optimization

2.1 Optimize two hyperparameters at once (12:09)
2.2 Refactor to separate out the optimization code (5:46)
2.3 Refactor to make optimization code object oriented (3:54)
2.4 Random search (6:54)

3. Evolutionary Powell's Method: An Experimental Optimizer

3.1 How Evolutionary Powell's method works
3.2 Evolutionary Powell's method in code (14:45)
3.3 Evolutionary Powell's' method results (9:26)

4. Code Optimization

4.1 Profiling (3:27)
4.2 Elimination and modification (5:35)
4.3 Cacheing and acceleration (5:27)
4.4 Pre-loading (4:42)
4.5 Parallelization (8:54)

5. Optimize the compressor

5.1 Hyperparameter optimization criterion: Compressed file size (6:31)
5.2 Neural architecture search setup (3:55)
5.3 Neural architecture search results (7:40)
5.4 Learning rate and initializer optimization (8:53)

6. Create an image compressor tool

6.1 API design for complete beginners (4:54)
6.2 API design for the image compressor (3:55)
6.3 API functions and arguments for the image compressor (9:18)
6.4 Image compressor tool code walkthrough, Part I (10:12)
6.5 Image compressor tool code walkthrough, Part II (5:44)
6.6 Test run the compressor and decompressor (4:50)
6.7 Inspect the results (5:16)
6.8 Improve the image quality (5:41)
6.9 Publish the Martian images case study (9:25)

6.1 API design for complete beginners

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