Published by Amazon Digital Services LLC - Kdp, 2025
ISBN 13: 9798291198339
Seller: PBShop.store UK, Fairford, GLOS, United Kingdom
US$ 28.21
Quantity: Over 20 available
Add to basketPAP. Condition: New. New Book. Shipped from UK. Established seller since 2000.
Published by Independently Published, 2025
ISBN 13: 9798291198339
Seller: Grand Eagle Retail, Bensenville, IL, U.S.A.
Paperback. Condition: new. Paperback. This all-in-one resource walks you through the full spectrum of machine learning. From foundational math to supervised, unsupervised, and reinforcement learning, it provides a thorough understanding of core ML and DL principles. Ideal for both beginners and advancing practitioners, it includes hands-on tools, practical algorithms, and insights into neural networks and optimization techniques. What's Inside? Regression, classification, and ensemble models Clustering, anomaly detection, and dimensionality reduction Reinforcement learning: Q-learning, DQNs, and MDPs Neural networks: MLPs, backpropagation, and activation functions Optimization: SGD, Adam, and regularization Transfer learning, feature extraction, and deployment Bias-variance tradeoff and model evaluation Why This Book?Because understanding the core mechanics of learning systems is key to building reliable, ethical, and high-performing AI models. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Published by Independently Published, 2025
ISBN 13: 9798291198339
Seller: CitiRetail, Stevenage, United Kingdom
US$ 32.41
Quantity: 1 available
Add to basketPaperback. Condition: new. Paperback. This all-in-one resource walks you through the full spectrum of machine learning. From foundational math to supervised, unsupervised, and reinforcement learning, it provides a thorough understanding of core ML and DL principles. Ideal for both beginners and advancing practitioners, it includes hands-on tools, practical algorithms, and insights into neural networks and optimization techniques. What's Inside? Regression, classification, and ensemble models Clustering, anomaly detection, and dimensionality reduction Reinforcement learning: Q-learning, DQNs, and MDPs Neural networks: MLPs, backpropagation, and activation functions Optimization: SGD, Adam, and regularization Transfer learning, feature extraction, and deployment Bias-variance tradeoff and model evaluation Why This Book?Because understanding the core mechanics of learning systems is key to building reliable, ethical, and high-performing AI models. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.