June 2016
Beginner to intermediate
304 pages
6h 24m
English
Overview
The "Python Machine Learning Cookbook" provides 100 practical, actionable recipes to help you apply machine learning in real-world situations. Through hands-on examples, you will learn how to implement machine learning algorithms using Python, covering areas like classification, clustering, and deep learning.
What this Book will help me do
- Master classification techniques for applications such as income bracket estimation.
- Apply deep learning methods to construct systems like biometric face recognitions.
- Analyze time series data to build predictive models.
- Gain insights into clustering data effectively for market segmentation.
- Use Python-based recommendation engines to improve user experience.
Author(s)
The authors, None Joshi and Vahid Mirjalili None, bring extensive experience in machine learning and Python programming. Their approach is to combine practical examples with clear explanations to guide readers through complex concepts.
Who is it for?
The ideal readers are Python programmers of any level looking to develop solid machine learning skills for real-world applications. Beginners in machine learning will find the clear explanations accessible, while intermediate users will benefit from the practical recipes.
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