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Bücher Englische Bücher Ratgeber & Freizeit Recht, Beruf, Finanzen Machine Learning Mastery:
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Machine Learning Mastery:
Rachel Bennett (Broschiert, Englisch)
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Beschreibung
Machine Learning Mastery Unlock the full power of machine learning and take your skills from beginner to advanced with a guide that blends foundational knowledge with future-facing insight. This comprehensive book is designed for those who are not satisfied with surface-level understanding. Whether you're just stepping into the world of algorithms or refining your ability to build intelligent… systems, this book is crafted to support your evolution into a true machine learning practitioner. From the math behind the models to ethical deployment in real-world environments, Machine Learning Mastery offers more than technical walkthroughs—it gives you the clarity and depth needed to think critically, adapt confidently, and build responsibly. With real examples, modern tools, and clear explanations, this book empowers you to understand the why behind every model, not just the how. Inside This Book, You'll Discover: The Foundations: Data, Algorithms, and Models Supervised Learning Demystified Understanding Neural Networks and Deep Learning Feature Engineering: Turning Data into Gold Overfitting, Underfitting, and the Bias-Variance Tradeoff Deploying Machine Learning Models in Production Ethics and Bias in Machine Learning Whether you're pursuing a career in AI, enhancing your current work, or preparing to innovate in a world powered by data, this book provides the roadmap. Each chapter builds on the last to help you make thoughtful, informed, and high-impact decisions with machine learning. Scroll Up and Grab Your Copy Today! Dieses Produkt haben wir gerade leider nicht auf Lager.
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Technische Daten
Erscheinungsdatum
19.03.2026
Sprache
Englisch
EAN
9783565340132
Herausgeber
epubli
Sonderedition
Nein
Autor
Rachel Bennett
Seitenanzahl
96
Auflage
3
Einbandart
Broschiert
Buch Untertitel
Build Real-World ML Projects with Python, Algorithms, and Data Science Fundamentals
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