Introduction to the day-to-day practice of machine learning, preparing you to successfully build and deploy powerful ML systems. It covers the art of ML project execution without overdosing you on academic theory and complex mathematics. Real-World Machine Learning will teach you the concepts and techniques you need to be a successful machine learning practitioner without overdosing you on abstract theory and complex mathematics. By working through immediately relevant examples in Python, you will build skills in data acquisition and modeling, classification, and regression. You will also explore the most important tasks like model validation, optimization, scalability, and real-time streaming. When you are done, you will be ready to successfully build, deploy, and maintain your own powerful ML systems.