The book covers the fundamentals of machine learning, including supervised and unsupervised learning, feature engineering, model selection, and evaluation. You will learn how to use Python libraries such as scikit-learn, TensorFlow, and PyTorch to build and evaluate machine learning models.
With a focus on practical examples and hands-on exercises, the book will help you build a solid foundation in machine learning and give you the confidence to tackle real-world projects. The book also includes a variety of case studies and projects that will help you apply the concepts you have learned to real-world situations.
Whether you're a beginner or an experienced programmer, this book is the perfect resource for anyone looking to expand their skill set and become a machine learning expert. With its clear explanations, step-by-step instructions, and hands-on exercises, this book will help you get up and running with Python machine learning in no time.
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