Description
Should I choose supervised learning or reinforcement learning? Which algorithm is best suited for my application? How does deep learning advance the capacities of problem-solving? If you have found yourself asking these questions, this book is specially developed for you.
The book will help readers understand the core concepts of machine learning and techniques to evaluate any machine learning model with ease. The book starts with the importance of machine learning by analyzing its impact on the global landscape. The book also covers Supervised and Unsupervised ML along with Reinforcement Learning. In subsequent chapters, the book explores these topics in even greater depth, evaluating the pros and cons of each and exploring important topics such as Bias-Variance Tradeoff, Clustering, and Dimensionality Reduction. The book also explains model evaluation techniques such as Cross-Validation and GridSearchCV. The book also features mind maps which help enhance the learning process by making it easier to learn and retain information.
This book is a one-stop solution for covering basic ML concepts in detail and the perfect stepping stone to becoming an expert in ML and deep learning and even applying them to
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