Solutions (math and code) of the exercises and problems from Michael Nielsen's book Neural Networks And Deep Learning (and adaptations to the code for Python 3 and Theano 1.0.3).
Here's where to find the solutions to exercises and problems:
- involving math:
notebooks
- involving code: implemented in
code
, discussed innotebooks
With links to nbviewer:
- Chapter 0: Update the code for Python 3
- Chapter 1: Using neural nets to recognize handwritten digits
- Chapter 2: How the backpropagation algorithm works
- Chapter 3: Improving the way neural networks learn
- Chapter 4: A visual proof that neural nets can compute any function
- Chapter 5: Why are deep neural networks hard to train?
- Chapter 6: Deep learning
So far, I've provided solutions to all exercises and problems, except:
- chap3 p8, p9
- chap4 p1 (c)
- chap6 p5, p7 (theano part)
I may have made mistakes, or provided incomplete or suboptimal solutions. And there are still some problems that I haven't solved. So direct improvements, or any suggestions, are much welcome!