Machine Learning by Mathematical Model and Practical Approach: Making ML Simple
Machine Learning by Mathematical Model and Practical Approach: Making ML Simple
English | 2024 | ASIN: B0D3LT5JS6 | 154 pages | Epub | 3.15 MB
English | 2024 | ASIN: B0D3LT5JS6 | 154 pages | Epub | 3.15 MB
Machine learning has rapidly evolved from a niche area of computer science to a pervasive technology shaping our everyday lives. From personalized recommendations on streaming platforms to autonomous vehicles navigating our roads, machine learning algorithms are powering a myriad of innovations across industries. Understanding the principles behind these algorithms is not just a professional asset but also a doorway to comprehend the technological marvels shaping our future.
This book is designed to be a comprehensive guide, covering fundamental concepts, advanced techniques, and real-world applications of machine learning. We start with the basics, laying a solid foundation by exploring essential algorithms such as linear regression, classification, and clustering. As we progress, we delve into more complex models like neural networks, support vector machines, and deep learning architectures.
But this book is not merely a catalogue of algorithms. It's a journey that goes beyond the equations and code snippets. We explore the underlying principles that govern machine learning, discussing topics such as overfitting, bias-variance trade-off etc.