Data Science, Machine Learning, Technology, Science, Mathematics.
bias-variance, overfitting, regularization etc.. 2. Dive into Deep Learning This book has a hands-on approach to Deep Learning. This is an interactive, deep learning book with code, math, and discussions with implementations with PyTorch, NumPy/MXNet, JAX, and TensorFlow. The authors of this book