Details about Machine Learning with Python Cookbook. Practical Solutions from Preprocessing to Deep Learning
Machine Learning with Python Cookbook PDF free download by Chris Albon (Github) – Over the last few years, machine learning has become embedded in a wide variety of day-to-day business, nonprofit, and government operations. As the popularity of machine learning increased, a cottage industry of high-quality literature that taught applied machine learning to practitioners developed. This literature has been highly successful in training an entire generation of data scientists and machine learning engineers. This literature also approached the topic of machine learning from the perspective of providing a learning resource to teach an individual what machine learning is and how it works. However, while fruitful, this approach left out a different perspective on the topic: the nuts and bolts of doing machine learning day to day.
That is the motivation of this book—not as a tome of machine learning knowledge for the student but as a wrench for the professional, to sit with dog-eared pages on desks ready to solve the practical day-to-day problems of a machine learning practitioner. More specifically, the book takes a task-based approach to machine learning, with almost 200 self-contained solutions (you can copy and paste the code and it’ll run) for the most common tasks a data scientist or machine learning engineer building a model will run into. The ultimate goal is for the book to be a reference for people building real machine learning systems. For example, imagine a reader has a JSON file containing 1,000 categorical and numerical features with missing data and categorical target vectors with imbalanced classes and wants an interpretable model.