The tools and syntax you need to code neural networks from day one.
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LICENSE
README.md
experiment_0_few_layers.ipynb
experiment_0_three_layer_sets.ipynb
experiment_1_with_dropout.ipynb
experiment_1_without_dropout.ipynb
experiment_2_regulizer_L2.ipynb
experiment_2_regulizer_whithout_L2.ipynb
experiment_2_without_regulizer.ipynb
experiment_3_high_batch_size.ipynb
experiment_3_low_batch_size.ipynb
experiment_4_learning_rate_high.ipynb
experiment_4_learning_rate_low.ipynb
experiment_4_learning_rate_normal.ipynb
floyd_requirements.txt
load_data.py
start-here.ipynb

README.md

Deep Learning 101

When I started learning deep learning I spent two weeks researching. I selected tools, compared cloud services, and researched online courses. In retrospect, I wish I could have built neural networks from day one. That’s what this article is set out to do. You don’t need any prerequisites, yet a basic understanding of Python, the command line, and Jupyter notebook will help.

This is the code experiments from the article.