I feel this book is the ideal companion for intermediate to advanced Python developers/data scientists. People who know pandas pretty well, and so are comfortable with numpy array operations too. They have probably used scikit-learn's fit/predict API in a black-box way, but have never quite had time to look at the code underneath.
I love "ML from Scratch" because it leverages my math and Python/numpy knowledge (even if some of it is rusty and half-forgotten) to show me high quality, well-commented, mathematically rigorously explanations of how I might have implemented the types of algorithms I use from sklearn. While the maths is formal, it is totally straightforward in its presentation.
It will definitely be my bedtime reading for the next few nights.
I feel this book is the ideal companion for intermediate to advanced Python developers/data scientists. People who know pandas pretty well, and so are comfortable with numpy array operations too. They have probably used scikit-learn's fit/predict API in a black-box way, but have never quite had time to look at the code underneath.
I love "ML from Scratch" because it leverages my math and Python/numpy knowledge (even if some of it is rusty and half-forgotten) to show me high quality, well-commented, mathematically rigorously explanations of how I might have implemented the types of algorithms I use from sklearn. While the maths is formal, it is totally straightforward in its presentation.
It will definitely be my bedtime reading for the next few nights.