Machine Learning with Python

Description

Machine Learning with Python: Principles and Practical Techniques (New Edition) by Parteek Bhatia is a comprehensive guide to modern AI. This book introduces fundamental machine learning concepts and their real-world applications using Python. It covers supervised, unsupervised, and reinforcement learning techniques with step-by-step coding examples. The book simplifies complex algorithms using clear explanations and hands-on programming exercises. It explores data preprocessing, model evaluation, and hyperparameter tuning for better performance.

Machine Learning with Python is designed for beginners, students, and professionals aiming to build expertise in AI development. The book provides practical insights into neural networks, decision trees, and deep learning frameworks. Readers will gain proficiency in data manipulation using Pandas and NumPy libraries. The book also includes detailed coverage of Scikit-Learn, TensorFlow, and Keras for advanced applications. It presents practical projects that enhance understanding and prepare readers for industry challenges.

With an emphasis on real-world use cases, the book bridges theory and implementation seamlessly. It equips readers with the skills to develop intelligent applications. The book discusses ethics, challenges, and future trends in machine learning. It also offers insights into handling imbalanced data and feature engineering techniques. The book’s structured approach ensures progressive learning with hands-on coding exercises. Each chapter includes quizzes, case studies, and exercises to reinforce concepts.

Machine Learning with Python is an essential resource for aspiring data scientists, AI researchers, and engineers. It offers a roadmap to mastering artificial intelligence using Python. The book’s updated edition includes the latest advancements in machine learning and deep learning. It is a must-read for those seeking a strong foundation in AI development.