Explore the fundamentals of Bayesian statistics and how it differs from frequentist approaches. Learn to think probabilistically about uncertainty and evidence.
Understanding how neural networks learn through backpropagation, with complete mathematical derivations and practical implementation from scratch. We have derived all the code from scratch in python and all the math was derived.