Machine Learning With Python For Everyone
Download Machine Learning With Python For Everyone PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Machine Learning With Python For Everyone book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages.
Machine Learning with Python for Everyone
Author: Mark Fenner
language: en
Publisher: Addison-Wesley Professional
Release Date: 2019-07-30
The Complete Beginner’s Guide to Understanding and Building Machine Learning Systems with Python Machine Learning with Python for Everyone will help you master the processes, patterns, and strategies you need to build effective learning systems, even if you’re an absolute beginner. If you can write some Python code, this book is for you, no matter how little college-level math you know. Principal instructor Mark E. Fenner relies on plain-English stories, pictures, and Python examples to communicate the ideas of machine learning. Mark begins by discussing machine learning and what it can do; introducing key mathematical and computational topics in an approachable manner; and walking you through the first steps in building, training, and evaluating learning systems. Step by step, you’ll fill out the components of a practical learning system, broaden your toolbox, and explore some of the field’s most sophisticated and exciting techniques. Whether you’re a student, analyst, scientist, or hobbyist, this guide’s insights will be applicable to every learning system you ever build or use. Understand machine learning algorithms, models, and core machine learning concepts Classify examples with classifiers, and quantify examples with regressors Realistically assess performance of machine learning systems Use feature engineering to smooth rough data into useful forms Chain multiple components into one system and tune its performance Apply machine learning techniques to images and text Connect the core concepts to neural networks and graphical models Leverage the Python scikit-learn library and other powerful tools Register your book for convenient access to downloads, updates, and/or corrections as they become available. See inside book for details.
Machine Learning in Python for Everyone
Author: Jonathan Wayne Korn, PhD
language: en
Publisher: Independently Published
Release Date: 2023-11-26
"Machine Learning in Python for Everyone" is your comprehensive guide to mastering machine learning with the Python programming language. Whether you're a novice looking to embark on your data science journey or an experienced practitioner aiming to refine your skills, this book provides a structured and hands-on approach to understanding and implementing machine learning concepts. Starting with the fundamentals, the book introduces you to machine learning algorithms, data manipulation, and analysis tools in Python. Through practical examples, you'll learn to collect, preprocess, and explore data, gaining insights into data-driven decision-making. The book covers regression, classification, and time series forecasting, equipping you with the knowledge to build predictive models effectively. You'll delve into model evaluation techniques, feature engineering, and model interpretation, ensuring you can not only create models but also optimize their performance. By the end of the book, you'll be proficient in various machine learning algorithms and visualization techniques, ready to tackle real-world challenges with confidence. "Machine Learning in Python for Everyone" is your gateway to unleashing the power of machine learning for practical applications in Python.
Python for Everyone
Author: Ellu P Martins
language: en
Publisher: Independently Published
Release Date: 2023-09-27
Python for Everyone is a detailed introduction to the Python programming language. This book is made for people who are just starting and can be used by anyone, regardless of their age or background. This text begins by explaining the fundamental rules and structure of Python programming language. Then, it progresses to more difficult subjects like analyzing data and training machines to learn automatically. The book has simple and easy-to-understand explanations. It also contains exercises and examples that are useful. It also has a dictionary of Python words and a list of places to learn more.