Paperback. Zustand: Good. No Jacket. Former library book; Pages can have notes/highlighting. Spine may show signs of wear. ~ ThriftBooks: Read More, Spend Less.
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In den Warenkorbpaperback. Zustand: Very Good. Orders shipped daily from the UK. Professional seller.
Anbieter: Late Knight Books, Philadelphia, PA, USA
Soft cover. Zustand: New. 2nd Edition. Since the first edition of "Data Science and Analytics with Python" we have witnessed an unprecedented explosion in the interest and development within the fields of Artificial Intelligence and Machine Learning. This surge has led to the widespread adoption of the book, not just among business practitioners, but also by universities as a key textbook. In response to this growth, this new edition builds upon the success of its predecessor, expanding several sections, updating the code to reflect the latest advancements in Python libraries and modules, and addressing the ever-evolving landscape of generative AI (GenAI). This updated edition ensures that the examples and exercises remain relevant by incorporating the latest features of popular libraries such as Scikit-learn, pandas, and Numpy. Additionally, new sections delve into cutting-edge topics like generative AI, reflecting the advancements and the expanding role these technologies play. This edition also addresses crucial issues of explainability, transparency, and fairness in AI. These topics have rightly gained significant attention in recent years. As AI integrates more deeply into various aspects of our lives, understanding and mitigating biases, ensuring fairness, and maintaining transparency become paramount. This book provides comprehensive coverage of these topics, offering practical insights and guidance for data scientists and analysts. Designed as a practical companion for data analysts and budding data scientists, this book assumes a working knowledge of programming and statistical modelling but aims to guide readers deeper into the wonders of data analytics and machine learning. Maintaining the book's structure, each chapter stands alone as much as possible, allowing readers to use it as a reference as well as a textbook. Whether revisiting fundamental concepts or diving into new, advanced topics, this book offers something valuable for every reader.
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Anbieter: Grand Eagle Retail, Bensenville, IL, USA
Paperback. Zustand: new. Paperback. Since the first edition of Data Science and Analytics with Python we have witnessed an unprecedented explosion in the interest and development within the fields of Artificial Intelligence and Machine Learning. This surge has led to the widespread adoption of the book, not just among business practitioners, but also by universities as a key textbook. In response to this growth, this new edition builds upon the success of its predecessor, expanding several sections, updating the code to reflect the latest advancements in Python libraries and modules, and addressing the ever-evolving landscape of generative AI (GenAI).This updated edition ensures that the examples and exercises remain relevant by incorporating the latest features of popular libraries such as Scikit-learn, pandas, and Numpy. Additionally, new sections delve into cutting-edge topics like generative AI, reflecting the advancements and the expanding role these technologies play. This edition also addresses crucial issues of explainability, transparency, and fairness in AI. These topics have rightly gained significant attention in recent years. As AI integrates more deeply into various aspects of our lives, understanding and mitigating biases, ensuring fairness, and maintaining transparency become paramount. This book provides comprehensive coverage of these topics, offering practical insights and guidance for data scientists and analysts.Designed as a practical companion for data analysts and budding data scientists, this book assumes a working knowledge of programming and statistical modelling but aims to guide readers deeper into the wonders of data analytics and machine learning. Maintaining the book's structure, each chapter stands alone as much as possible, allowing readers to use it as a reference as well as a textbook. Whether revisiting fundamental concepts or diving into new, advanced topics, this book offers something valuable for every reader. Since the first edition of Data Science and Analytics with Python we have witnessed an unprecedented explosion in the interest and development within the fields of Artificial Intelligence and Machine Learning. This has led to book becoming a key textbook among practitioners and students. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Zustand: As New. Unread book in perfect condition.
PAP. Zustand: New. New Book. Shipped from UK. Established seller since 2000.
Anbieter: Books Puddle, New York, NY, USA
Zustand: New. 2nd edition NO-PA16APR2015-KAP.
Anbieter: PBShop.store UK, Fairford, GLOS, Vereinigtes Königreich
EUR 63,85
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In den WarenkorbPAP. Zustand: New. New Book. Shipped from UK. Established seller since 2000.
Anbieter: Majestic Books, Hounslow, Vereinigtes Königreich
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Anbieter: Biblios, Frankfurt am main, HESSE, Deutschland
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In den WarenkorbZustand: New.
Sprache: Englisch
Verlag: Taylor and Francis Ltd, GB, 2025
ISBN 10: 1032772492 ISBN 13: 9781032772493
Anbieter: Rarewaves.com USA, London, LONDO, Vereinigtes Königreich
EUR 81,23
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In den WarenkorbPaperback. Zustand: New. Since the first edition of "Data Science and Analytics with Python" we have witnessed an unprecedented explosion in the interest and development within the fields of Artificial Intelligence and Machine Learning. This surge has led to the widespread adoption of the book, not just among business practitioners, but also by universities as a key textbook. In response to this growth, this new edition builds upon the success of its predecessor, expanding several sections, updating the code to reflect the latest advancements in Python libraries and modules, and addressing the ever-evolving landscape of generative AI (GenAI).This updated edition ensures that the examples and exercises remain relevant by incorporating the latest features of popular libraries such as Scikit-learn, pandas, and Numpy. Additionally, new sections delve into cutting-edge topics like generative AI, reflecting the advancements and the expanding role these technologies play. This edition also addresses crucial issues of explainability, transparency, and fairness in AI. These topics have rightly gained significant attention in recent years. As AI integrates more deeply into various aspects of our lives, understanding and mitigating biases, ensuring fairness, and maintaining transparency become paramount. This book provides comprehensive coverage of these topics, offering practical insights and guidance for data scientists and analysts.Designed as a practical companion for data analysts and budding data scientists, this book assumes a working knowledge of programming and statistical modelling but aims to guide readers deeper into the wonders of data analytics and machine learning. Maintaining the book's structure, each chapter stands alone as much as possible, allowing readers to use it as a reference as well as a textbook. Whether revisiting fundamental concepts or diving into new, advanced topics, this book offers something valuable for every reader.
Anbieter: Chiron Media, Wallingford, Vereinigtes Königreich
EUR 63,90
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In den Warenkorbpaperback. Zustand: New.
Anbieter: Ria Christie Collections, Uxbridge, Vereinigtes Königreich
EUR 69,06
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In den WarenkorbZustand: New. In.
Sprache: Englisch
Verlag: Taylor and Francis Ltd, GB, 2025
ISBN 10: 1032772492 ISBN 13: 9781032772493
Anbieter: Rarewaves USA, OSWEGO, IL, USA
Paperback. Zustand: New. Since the first edition of "Data Science and Analytics with Python" we have witnessed an unprecedented explosion in the interest and development within the fields of Artificial Intelligence and Machine Learning. This surge has led to the widespread adoption of the book, not just among business practitioners, but also by universities as a key textbook. In response to this growth, this new edition builds upon the success of its predecessor, expanding several sections, updating the code to reflect the latest advancements in Python libraries and modules, and addressing the ever-evolving landscape of generative AI (GenAI).This updated edition ensures that the examples and exercises remain relevant by incorporating the latest features of popular libraries such as Scikit-learn, pandas, and Numpy. Additionally, new sections delve into cutting-edge topics like generative AI, reflecting the advancements and the expanding role these technologies play. This edition also addresses crucial issues of explainability, transparency, and fairness in AI. These topics have rightly gained significant attention in recent years. As AI integrates more deeply into various aspects of our lives, understanding and mitigating biases, ensuring fairness, and maintaining transparency become paramount. This book provides comprehensive coverage of these topics, offering practical insights and guidance for data scientists and analysts.Designed as a practical companion for data analysts and budding data scientists, this book assumes a working knowledge of programming and statistical modelling but aims to guide readers deeper into the wonders of data analytics and machine learning. Maintaining the book's structure, each chapter stands alone as much as possible, allowing readers to use it as a reference as well as a textbook. Whether revisiting fundamental concepts or diving into new, advanced topics, this book offers something valuable for every reader.
Zustand: New. 2025. 2nd Edition. paperback. . . . . .
Anbieter: GreatBookPricesUK, Woodford Green, Vereinigtes Königreich
EUR 66,73
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In den WarenkorbZustand: New.
Anbieter: GreatBookPricesUK, Woodford Green, Vereinigtes Königreich
EUR 67,25
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In den WarenkorbZustand: As New. Unread book in perfect condition.