Python Machine Learning By Example: The easiest way to get into machine learning
ISBN-13:
9781783553112
ISBN-10:
1783553111
Author:
Yuxi (Hayden) Liu
Publication date:
2017
Publisher:
Packt Publishing
Format:
Paperback
254 pages
Category:
AI & Machine Learning
,
Computer Science
FREE US shipping
Book details
ISBN-13:
9781783553112
ISBN-10:
1783553111
Author:
Yuxi (Hayden) Liu
Publication date:
2017
Publisher:
Packt Publishing
Format:
Paperback
254 pages
Category:
AI & Machine Learning
,
Computer Science
Summary
Python Machine Learning By Example: The easiest way to get into machine learning (ISBN-13: 9781783553112 and ISBN-10: 1783553111), written by authors
Yuxi (Hayden) Liu, was published by Packt Publishing in 2017.
With an overall rating of 4.4 stars, it's a notable title among other
AI & Machine Learning
(Computer Science) books. You can easily purchase or rent Python Machine Learning By Example: The easiest way to get into machine learning (Paperback) from BooksRun,
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And, if you're looking to sell your copy, our current buyback offer is $1.86.
Description
Key Features
- Learn the fundamentals of machine learning and build your own intelligent applications
- Master the art of building your own machine learning systems with this example-based practical guide
- Work with important classification and regression algorithms and other machine learning techniques
This book starts with an introduction to machine learning and the Python language and shows you how to complete the setup. Moving ahead, you will learn all the important concepts such as, exploratory data analysis, data preprocessing, feature extraction, data visualization and clustering, classification, regression and model performance evaluation. With the help of various projects included, you will find it intriguing to acquire the mechanics of several important machine learning algorithms - they are no more obscure as they thought. Also, you will be guided step by step to build your own models from scratch. Toward the end, you will gather a broad picture of the machine learning ecosystem and best practices of applying machine learning techniques.
Through this book, you will learn to tackle data-driven problems and implement your solutions with the powerful yet simple language, Python. Interesting and easy-to-follow examples, to name some, news topic classification, spam email detection, online ad click-through prediction, stock prices forecast, will keep you glued till you reach your goal.
What you will learn
- Exploit the power of Python to handle data extraction, manipulation, and exploration techniques
- Use Python to visualize data spread across multiple dimensions and extract useful features
- Dive deep into the world of analytics to predict situations correctly
- Implement machine learning classification and regression algorithms from scratch in Python
- Be amazed to see the algorithms in action
- Evaluate the performance of a machine learning model and optimize it
- Solve interesting real-world problems using machine learning and Python as the journey unfolds
Table of Contents
- Getting Started with Python and Machine Learning
- Exploring the 20 newsgroups data set
- Spam email detection with Naïve Bayes
- News topic classification with Support Vector Machine
- Click-through prediction with tree-based algorithms
- Click-through rate prediction with logistic regression
- Stock prices prediction with regression algorithms
- Best practices
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