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Machine Learning for the Web

Machine Learning for the Web

By : Steve Essinger, Isoni
4.5 (27)
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Machine Learning for the Web

Machine Learning for the Web

4.5 (27)
By: Steve Essinger, Isoni

Overview of this book

Python is a general purpose and also a comparatively easy to learn programming language. Hence it is the language of choice for data scientists to prototype, visualize, and run data analyses on small and medium-sized data sets. This is a unique book that helps bridge the gap between machine learning and web development. It focuses on the difficulties of implementing predictive analytics in web applications. We focus on the Python language, frameworks, tools, and libraries, showing you how to build a machine learning system. You will explore the core machine learning concepts and then develop and deploy the data into a web application using the Django framework. You will also learn to carry out web, document, and server mining tasks, and build recommendation engines. Later, you will explore Python’s impressive Django framework and will find out how to build a modern simple web app with machine learning features.
Table of Contents (10 chapters)
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9
Index

Chapter 2. Unsupervised Machine Learning

As we have seen in the Chapter 1, Introduction to Practical Machine Learning Using Python, unsupervised learning is designed to provide insightful information on data unlabeled date. In many cases, a large dataset (both in terms of number of points and number of features) is unstructured and does not present any information at first sight, so these techniques are used to highlight hidden structures on data (clustering) or to reduce its complexity without losing relevant information (dimensionality reduction). This chapter will focus on the main clustering algorithms (the first part of the chapter) and dimensionality reduction methods (the second part of the chapter). The differences and advantages of the methods will be highlighted by providing a practical example using Python libraries. All of the code will be available on the author's GitHub profile, in the https://github.com/ai2010/machine_learning_for_the_web/tree/master/chapter_2...

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Machine Learning for the Web
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