Machine Learning Pocket Reference

Machine learning and data science are very popular right now and are fast-moving targets. I have worked with Python and data for most of my career and wanted to have a physical book that could provide a reference for the common methods that I have been using in industry and teaching during workshops to solve structured machine learning problems. This book is what I believe is the best collection of resources and examples for attacking a predictive modeling task if you have structured data. There are many libraries that perform a portion of the tasks required and I have tried to incorporate those that I have found useful as I have applied these techniques in consulting or industry work. Many may lament the lack of deep learning techniques. Those could be a book by themselves. I also prefer simpler techniques and others in industry seem to agree. Deep learning for unstructured data (video, audio, images), and powerful tools like XGBoost for structured data. I hope this book serves as a useful reference for you to solve pressing problems.