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Paperback. Etat : new. Paperback. Hands-On Python and Scikit-Learn: A Practical Guide to Machine LearningMaster Machine Learning with Python and Scikit-LearnAre you ready to dive into the world of machine learning? Hands-On Python and Scikit-Learn: A Practical Guide to Machine Learning is your ultimate guide to mastering data preprocessing, model building, and evaluation using Python and Scikit-Learn.Why This Book? Comprehensive & Hands-On - Covers supervised and unsupervised learning, model evaluation, and workflow automation. Real-World Applications - Learn to build models for predictive analytics, fraud detection, sentiment analysis, and more. Optimized for Python - Uses Python 3.x for efficient and scalable implementations. For Beginners & Professionals - Suitable for students, developers, and data scientists looking to master Scikit-Learn.What You'll Learn Setting up Scikit-Learn for machine learning projects Data preprocessing, feature selection, and transformation Implementing linear regression, decision trees, SVMs, and ensemble models Hyperparameter tuning and model optimization techniques Clustering, anomaly detection, and dimensionality reduction Building real-world machine learning applicationsWho Should Read This Book? This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Taschenbuch. Etat : Neu. Neuware - Why This Book.

Paperback. Etat : new. Paperback. Hands-On Python and Scikit-Learn: A Practical Guide to Machine LearningMaster Machine Learning with Python and Scikit-LearnAre you ready to dive into the world of machine learning? Hands-On Python and Scikit-Learn: A Practical Guide to Machine Learning is your ultimate guide to mastering data preprocessing, model building, and evaluation using Python and Scikit-Learn.Why This Book? Comprehensive & Hands-On - Covers supervised and unsupervised learning, model evaluation, and workflow automation. Real-World Applications - Learn to build models for predictive analytics, fraud detection, sentiment analysis, and more. Optimized for Python - Uses Python 3.x for efficient and scalable implementations. For Beginners & Professionals - Suitable for students, developers, and data scientists looking to master Scikit-Learn.What You'll Learn Setting up Scikit-Learn for machine learning projects Data preprocessing, feature selection, and transformation Implementing linear regression, decision trees, SVMs, and ensemble models Hyperparameter tuning and model optimization techniques Clustering, anomaly detection, and dimensionality reduction Building real-world machine learning applicationsWho Should Read This Book? This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.