This book provides a structured and accessible pathway into the world of machine learning.1 Beginning with fundamental concepts and progressing through advanced topics, it covers essential Python libraries, mathematical foundations, and practical applications. The book delves into supervised and unsupervised learning, natural language processing, computer vision, time series analysis, and recommender systems.2 It also addresses critical aspects of model deployment, ethical considerations, and future trends, including reinforcement learning, GANs, and AutoML. With practical examples, troubleshooting tips, and a glossary, this resource empowers readers to build and deploy effective machine learning models while understanding the broader implications of AI.
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Paperback. Condition: new. Paperback. This book provides a structured and accessible pathway into the world of machine learning.1 Beginning with fundamental concepts and progressing through advanced topics, it covers essential Python libraries, mathematical foundations, and practical applications. The book delves into supervised and unsupervised learning, natural language processing, computer vision, time series analysis, and recommender systems.2 It also addresses critical aspects of model deployment, ethical considerations, and future trends, including reinforcement learning, GANs, and AutoML. With practical examples, troubleshooting tips, and a glossary, this resource empowers readers to build and deploy effective machine learning models while understanding the broader implications of AI. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Seller Inventory # 9798312194982
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Paperback. Condition: new. Paperback. This book provides a structured and accessible pathway into the world of machine learning.1 Beginning with fundamental concepts and progressing through advanced topics, it covers essential Python libraries, mathematical foundations, and practical applications. The book delves into supervised and unsupervised learning, natural language processing, computer vision, time series analysis, and recommender systems.2 It also addresses critical aspects of model deployment, ethical considerations, and future trends, including reinforcement learning, GANs, and AutoML. With practical examples, troubleshooting tips, and a glossary, this resource empowers readers to build and deploy effective machine learning models while understanding the broader implications of AI. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9798312194982
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