Introduction to Machine Learning and Tools

Supervised Learning with Scikit-Learn

Unsupervised Learning and Preprocessing

Understanding Deep Learning with Keras

Neural Networks and Convolutional Neural Networks

Reinforcement Learning

Advanced Techniques in Machine Learning

Distributed TensorFlow and Model Deployment

Exploring Case Studies and Real-Time Applications

Ethics and Future of Machine Learning

This book is a comprehensive guide to Machine Learning with practical applications using Python-based tools such as Sklearn, Keras, and TensorFlow. It introduces the fundamental concepts of Machine Learning, explores various tools and techniques for building intelligent systems, and offers hands-on experience with real-world projects using Scikit-Learn, Keras, and TensorFlow.

technology

non_fiction

Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems