Verlag: Amazon Digital Services LLC - Kdp, 2025
ISBN 13: 9798291198339
Anbieter: PBShop.store UK, Fairford, GLOS, Vereinigtes Königreich
EUR 24,70
Anzahl: Mehr als 20 verfügbar
In den WarenkorbPAP. Zustand: New. New Book. Shipped from UK. Established seller since 2000.
Verlag: Independently Published, 2025
ISBN 13: 9798291198339
Anbieter: Grand Eagle Retail, Bensenville, IL, USA
Paperback. Zustand: 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.
Verlag: Independently Published, 2025
ISBN 13: 9798291198339
Anbieter: CitiRetail, Stevenage, Vereinigtes Königreich
EUR 28,37
Anzahl: 1 verfügbar
In den WarenkorbPaperback. Zustand: 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.