Unlike dense academic textbooks, Bernard focuses on accessibility and reproducibility. The book is structured as a , where explanations are closely followed by functional code.
Most textbooks stop at the algorithm. Bernard covers overfitting and cross-validation early. He wants you to know why a model can be 99% accurate on training data and 50% accurate in the real world. introduction to machine learning etienne bernard pdf