I am intermediate/advanced in Python and new to machine learning. Most of what I know about deep learning I learned through Deep Learning with Python by François Chollet. I am trying to do image classification and semantic segmentation on some of my own data (pictures I generate digitally). However, I am having a hard time adapting the examples in the book because there are many lines of code in the examples that aren't explained. The book is a broad overview with a few examples, and this is also what I find in most webpages and tutorials on the internet.

On the other hand, I'm finding it hard to learn directly from the Keras and PyTorch documentation because it is specific, and has "jargon" that I'm not familiar with yet.

What are some resources to help a deep learning newby to write their own network? Books, websites, lecture series, notes, etc. all welcome.



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