+- Softwarez.Info - Software's World! (https://softwarez.info)
+-- Forum: Library Zone (https://softwarez.info/Forum-Library-Zone)
+--- Forum: E-Books (https://softwarez.info/Forum-E-Books)
+--- Thread: Machine Learning Made Easy with Python (/Thread-Machine-Learning-Made-Easy-with-Python)
Machine Learning Made Easy with Python - ebooks1001 - 11-15-2024
![[Image: 2ba2195a0644ba7942fae23188515e64.webp]](https://i124.fastpic.org/big/2024/1114/64/2ba2195a0644ba7942fae23188515e64.webp)
Free Download Machine Learning Made Easy with Python (Mastering Machine Learning) by Jamie Flux
English | July 25, 2024 | ISBN: N/A | ASIN: B0DB78GCKK | 334 pages | PDF | 5.83 Mb
Discover the key concepts of machine learning with "Machine Learning Made Easy". This comprehensive guide covers a wide range of topics, from linear regression and logistic regression to decision trees, support vector machines, and neural networks. With practical examples and Python code, this book will help you understand and implement machine learning algorithms with ease.
Key Features:
- Step-by-step explanations of machine learning concepts
- Practical examples and real-world datasets
- Python code implementation for each algorithm
- Multiple choice review questions for each chapter
- Clear and concise explanations for both beginners and experienced learners
Book Description:
"Machine Learning Made Easy" is designed to make the complex world of machine learning accessible to everyone. Whether you're a beginner starting your journey into this exciting field or an experienced practitioner looking to expand your knowledge, this book has something for you. Each chapter introduces a different machine learning algorithm and provides a step-by-step explanation of its implementation. With practical examples and Python code, you'll learn how to apply these algorithms to real-world problems.
What You Will Learn:
- Understand the basic concepts of machine learning
- Implement linear regression and logistic regression
- Build decision trees and random forests
- Discover the power of support vector machines and K-nearest neighbors
- Explore deep learning with neural networks and convolutional neural networks
- Master advanced techniques like hierarchical clustering and principal component analysis
- Apply reinforcement learning and genetic algorithms to solve complex problems
Who This Book Is For:
This book is for anyone interested in learning machine learning, including data scientists, software engineers, and students. Whether you're a beginner or have some experience in the field, this book will provide you with the knowledge and skills to implement machine learning algorithms effectively. The Python code and multiple choice review questions for each chapter make this book an ideal learning tool for self-study or classroom use.
Recommend Download Link Hight Speed | Please Say Thanks Keep Topic Live
Links are Interchangeable - Single Extraction