The Comprehensive Beginner’s Guide to Understanding and Building Machine Learning Systems with Python
Machine Learning with Python for Everyone, (PDF) will help you master the patterns, processes, and strategies you need to build useful learning systems, even if you’re a complete beginner. If you can write some Python code, this ebook is for you, no matter how little college-level math you know. Principal instructor Mark E. Fenner depends on plain-English stories, pictures, and Python examples to convey the ideas of machine learning.
Mark starts by discussing machine learning and what it can do; introducing key mathematical and computational topics in a friendly manner; and walking you through the first steps in building, training, and assessing learning systems. Step by step, you’ll fill out the factors of a practical learning system, broaden your toolbox, and discover some of the field’s most sophisticated and exciting techniques. Whether you’re an analyst, college student, scientist, or hobbyist, this guide’s perceptions will be applicable to every learning system you ever build or use.
- Employ machine learning techniques to images and text
- Link the core concepts to neural networks and graphical models
- Leverage the Python sci-kit-learn library and other powerful tools
- Use feature engineering to smooth rough data into valuable forms
- Realistically evaluate the performance of machine learning systems
- Chain multiple components into one system and tune its performance
- Classify examples with classifiers, and quantify examples with regressors
- Understand machine learning algorithms, models, and core machine learning concepts
NOTE: The product only includes the ebook, Machine Learning with Python for Everyone in PDF. No access codes are included.