Machine Learning : A Hands-on Practice & Path to Professional

By Dr. Anil Kumar, Dr. Vikram Bali, Dr. Sanjay Kumar

The book "Machine Learning: A Hands-on Practice & Path to Professional" serves as a comprehensive guide for learners, practitioners, and professionals looking to gain expertise in machine learning. It introduces the fundamental concepts of machine learning, providing a strong theoretical foundation while emphasizing practical implementation. The book covers key topics such as supervised and unsupervised learning, classification, regression, clustering, and deep learning techniques. It walks readers through essential algorithms like decision trees, support vector machines, k-nearest neighbors, and neural networks, ensuring a thorough understanding of their applications and optimization techniques. A significant focus is given to hands-on learning , where the book guides readers in implementing machine learning models using popular frameworks like TensorFlow, Scikit-Learn, and PyTorch. Through step-by-step coding exercises, readers gain practical experience in data preprocessing, model training, hyperparameter tuning, and performance evaluation. The book also explores essential data science concepts, including feature engineering, dimensionality reduction, and model interpretability, which are crucial for building efficient machine learning systems. Beyond theoretical knowledge, the book prepares readers for a professional career in machine learning by discussing real-world applications across industries such as healthcare, finance, e-commerce, and automation. It provides insights into deploying machine learning models in production, addressing challenges related to scalability, bias, and ethical AI. The book also introduces best practices for debugging machine learning models, optimizing computation costs, and handling large-scale datasets. Furthermore, the book covers advanced topics such as reinforcement learning, generative models, and natural language processing (NLP), equipping readers with the knowledge required to tackle complex machine learning problems. It also highlights the latest trends in AI and ML, helping professionals stay updated with emerging technologies. Designed for beginners and professionals alike, this book bridges the gap between academic learning and industry requirements by combining theoretical depth with hands-on exercises. Whether a reader is looking to start a career in data science or advance their expertise in AI, this book serves as a practical roadmap to becoming a machine learning professional .

• Format: Hardcover
• Language: English
• ISBN: B0F5X4ZGSQ
• ISBN13: 9798313774817
• Release Date: April 2025
• Publisher: Independently published
• Length: 302 Pages
• Dimensions: 9.0" x 0.9" x 6.0"