Applied Unsupervised Learning with Python: Discover hidden patterns and relationships in unstructured data with Python

Price: $30.39
(as of Dec 24,2024 02:19:23 UTC – Details)

ASIN ‏ : ‎ B07KX42TXY
Publisher ‏ : ‎ Packt Publishing; 1st edition (May 28, 2019)
Publication date ‏ : ‎ May 28, 2019
Language ‏ : ‎ English
File size ‏ : ‎ 28697 KB
Text-to-Speech ‏ : ‎ Enabled
Screen Reader ‏ : ‎ Supported
Enhanced typesetting ‏ : ‎ Enabled
X-Ray ‏ : ‎ Not Enabled
Word Wise ‏ : ‎ Not Enabled
Print length ‏ : ‎ 482 pages

Unsupervised learning is a powerful technique in machine learning that allows us to uncover hidden patterns and relationships within unstructured data. In this post, we will explore how to apply unsupervised learning techniques with Python to discover these hidden insights.

Python is a popular programming language for data analysis and machine learning due to its simplicity and extensive libraries. In this post, we will focus on using Python libraries such as scikit-learn and pandas to perform unsupervised learning tasks.

We will start by discussing the basics of unsupervised learning and the different types of techniques that can be applied, such as clustering and dimensionality reduction. We will then provide a step-by-step guide on how to implement these techniques using Python and demonstrate how they can be used to uncover hidden patterns and relationships in unstructured data.

By the end of this post, you will have a solid understanding of how to apply unsupervised learning techniques with Python and be able to use them to gain valuable insights from your data. So, let’s dive in and discover the hidden patterns and relationships in your data with Python!
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