Notes
Reinforcement Learning
Chapter notes for revision, starting with Markov Decision Processes, policies, and the discount factor.
Open notesEpochs
My notes on the things I'm learning — reinforcement learning, the maths behind models, and more. Each epoch is one more pass of understanding.
Learning Pandas: Working with Tabular Data
My notes on pandas - the Series and DataFrame, how indexing really works, and the groupby split-apply-combine pattern that finally made data wrangling click.
Learning NumPy: Arrays and Vectorization
My notes on NumPy - the ndarray, why vectorization beats Python loops, and how broadcasting lets arrays of different shapes work together.
Learning PyTorch: Tensors, Autograd & the Training Loop
My notes on PyTorch - tensors as NumPy-with-gradients, how autograd builds the backward pass for you, and the five steps every training loop repeats.