Machine Learning Mastery:
Rachel Bennett
This audiobook is narrated by a digital voice.
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 ModelsSupervised Learning DemystifiedUnderstanding Neural Networks and Deep LearningFeature Engineering: Turning Data into GoldOverfitting, Underfitting, and the Bias-Variance TradeoffDeploying Machine Learning Models in ProductionEthics and Bias in Machine LearningWhether 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!
Duration - 2h 43m.
Author - Rachel Bennett.
Narrator - Digital Voice Marcus G.
Published Date - Saturday, 25 January 2025.
Copyright - © 2025 Rachel Bennett ©.
Location:
United States
Description:
This audiobook is narrated by a digital voice. 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 ModelsSupervised Learning DemystifiedUnderstanding Neural Networks and Deep LearningFeature Engineering: Turning Data into GoldOverfitting, Underfitting, and the Bias-Variance TradeoffDeploying Machine Learning Models in ProductionEthics and Bias in Machine LearningWhether 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! Duration - 2h 43m. Author - Rachel Bennett. Narrator - Digital Voice Marcus G. Published Date - Saturday, 25 January 2025. Copyright - © 2025 Rachel Bennett ©.
Language:
English
Intro
Duration:00:00:11
Beginning
Duration:00:02:46
Introduction to Machine Learning and Its Real-World Impact
Duration:00:08:38
The Foundations: Data, Algorithms, and Models
Duration:00:09:46
Supervised Learning Demystified
Duration:00:10:15
Diving into Unsupervised Learning
Duration:00:11:06
The Power of Semi-Supervised and Self-Supervised Learning
Duration:00:10:56
Understanding Neural Networks and Deep Learning
Duration:00:10:51
Feature Engineering: Turning Data into Gold
Duration:00:10:44
Model Evaluation and Performance Metrics
Duration:00:10:52
Overfitting, Underfitting, and the Bias-Variance Tradeoff
Duration:00:09:47
Hyperparameter Tuning and Model Optimization
Duration:00:10:16
Deploying Machine Learning Models in Production
Duration:00:11:18
Tools, Libraries, and Frameworks Every ML Engineer Should Know
Duration:00:11:13
Ethics and Bias in Machine Learning
Duration:00:10:52
Emerging Trends and the Future of Machine Learning
Duration:00:11:57
Final Thoughts: Becoming a Machine Learning Master
Duration:00:09:15
Conclusion
Duration:00:02:42