Items related to Machine Learning (Spanish Edition)
Synopsis
Machine Learning for Undergraduate Students (Second Edition) is a comprehensive guide designed to make the complex world of machine learning accessible to beginners. This book introduces foundational concepts, starting with the need for machine learning, its relationship with other fields, and its diverse applications. Through a structured exploration of essential topics, readers will gain a clear understanding of data analysis, including univariate, bivariate, and multivariate statistics, as well as techniques like feature engineering and dimensionality reduction.
Building on these basics, the book delves into core machine learning methodologies. Topics include similarity-based learning, regression analysis, decision tree algorithms, and Bayesian learning. The chapters also introduce artificial neural networks, explaining their biological inspiration, architecture, and applications. Advanced subjects such as clustering algorithms, proximity measures, and reinforcement learning-covering Q-Learning and SARSA-are presented with clarity, ensuring a thorough understanding of each concept.
The enhanced second edition features two appendices. Appendix A covers a description of learning paradigms that covers batch and online learning approaches, along with advanced few-shot and one-shot learning techniques. Learners explore how models adapt to different data scenarios-from processing complete datasets to learning from just one or a few examples-using various learning styles, including metric learning, meta-learning, prototype-based methods, and attention-based approaches across diverse applications in healthcare, robotics, and computer vision. Appendix B dwells on several numerical exercises for the learner to practice.
"synopsis" may belong to another edition of this title.
Search results for Machine Learning (Spanish Edition)
Stock Image
Machine Learning
Seller: PBShop.store UK, Fairford, GLOS, United Kingdom
Seller rating 5 out of 5 stars
PAP. Condition: New. New Book. Shipped from UK. Established seller since 2000. Seller Inventory # L2-9789374268520
Buy New
US$ 29.37
US$ 7.94 shipping
Ships from United Kingdom to U.S.A.
Ships from United Kingdom to U.S.A.
Quantity: Over 20 available
Stock Image
Machine Learning
ISBN 10: 9374268523
ISBN 13: 9789374268520
New
Seller: Books Puddle, New York, NY, U.S.A.
Seller rating 4 out of 5 stars
Condition: New. Seller Inventory # 26406787015
Stock Image
Machine Learning
ISBN 10: 9374268523
ISBN 13: 9789374268520
New
Seller: Majestic Books, Hounslow, United Kingdom
Seller rating 4 out of 5 stars
Condition: New. Seller Inventory # 407415832
Buy New
US$ 38.52
US$ 8.79 shipping
Ships from United Kingdom to U.S.A.
Ships from United Kingdom to U.S.A.
Quantity: 4 available
Stock Image
Machine Learning
ISBN 10: 9374268523
ISBN 13: 9789374268520
New
Seller: Biblios, Frankfurt am main, HESSE, Germany
Seller rating 4 out of 5 stars
Condition: New. Seller Inventory # 18406787021
Buy New
US$ 42.03
US$ 11.51 shipping
Ships from Germany to U.S.A.
Ships from Germany to U.S.A.
Quantity: 4 available
Stock Image
Machine Learning (Paperback)
Print on DemandSeller: CitiRetail, Stevenage, United Kingdom
Seller rating 5 out of 5 stars
Paperback. Condition: new. Paperback. Machine Learning for Undergraduate Students (Second Edition) is a comprehensive guide designed to make the complex world of machine learning accessible to beginners. This book introduces foundational concepts, starting with the need for machine learning, its relationship with other fields, and its diverse applications. Through a structured exploration of essential topics, readers will gain a clear understanding of data analysis, including univariate, bivariate, and multivariate statistics, as well as techniques like feature engineering and dimensionality reduction.Building on these basics, the book delves into core machine learning methodologies. Topics include similarity-based learning, regression analysis, decision tree algorithms, and Bayesian learning. The chapters also introduce artificial neural networks, explaining their biological inspiration, architecture, and applications. Advanced subjects such as clustering algorithms, proximity measures, and reinforcement learning-covering Q-Learning and SARSA-are presented with clarity, ensuring a thorough understanding of each concept.The enhanced second edition features two appendices. Appendix A covers a description of learning paradigms that covers batch and online learning approaches, along with advanced few-shot and one-shot learning techniques. Learners explore how models adapt to different data scenarios-from processing complete datasets to learning from just one or a few examples-using various learning styles, including metric learning, meta-learning, prototype-based methods, and attention-based approaches across diverse applications in healthcare, robotics, and computer vision. Appendix B dwells on several numerical exercises for the learner to practice. Machine Learning for Undergraduate Students (Second Edition) This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Seller Inventory # 9789374268520
Buy New
US$ 34.12
US$ 50.05 shipping
Ships from United Kingdom to U.S.A.
Ships from United Kingdom to U.S.A.
Quantity: 1 available
Stock Image
Machine Learning (Paperback)
Print on DemandSeller: AussieBookSeller, Truganina, VIC, Australia
Seller rating 5 out of 5 stars
Paperback. Condition: new. Paperback. Machine Learning for Undergraduate Students (Second Edition) is a comprehensive guide designed to make the complex world of machine learning accessible to beginners. This book introduces foundational concepts, starting with the need for machine learning, its relationship with other fields, and its diverse applications. Through a structured exploration of essential topics, readers will gain a clear understanding of data analysis, including univariate, bivariate, and multivariate statistics, as well as techniques like feature engineering and dimensionality reduction.Building on these basics, the book delves into core machine learning methodologies. Topics include similarity-based learning, regression analysis, decision tree algorithms, and Bayesian learning. The chapters also introduce artificial neural networks, explaining their biological inspiration, architecture, and applications. Advanced subjects such as clustering algorithms, proximity measures, and reinforcement learning-covering Q-Learning and SARSA-are presented with clarity, ensuring a thorough understanding of each concept.The enhanced second edition features two appendices. Appendix A covers a description of learning paradigms that covers batch and online learning approaches, along with advanced few-shot and one-shot learning techniques. Learners explore how models adapt to different data scenarios-from processing complete datasets to learning from just one or a few examples-using various learning styles, including metric learning, meta-learning, prototype-based methods, and attention-based approaches across diverse applications in healthcare, robotics, and computer vision. Appendix B dwells on several numerical exercises for the learner to practice. Machine Learning for Undergraduate Students (Second Edition) This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. Seller Inventory # 9789374268520
Buy New
US$ 47.52
US$ 37.00 shipping
Ships from Australia to U.S.A.
Ships from Australia to U.S.A.
Quantity: 1 available