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Machine Learning for the Web Cover

Machine Learning for the Web

Gaining insight and intelligence from the internet with Python

Publisher:Packt Publishing Limited
By: Steve Essinger and  Andrea Isoni  
Paid access
|Aug 2016
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Explore the web and make smarter predictions using Python

Key Features

  • Targets two big and prominent markets where sophisticated web apps are of need and importance.
  • Practical examples of building machine learning web application, which are easy to follow and replicate.
  • A comprehensive tutorial on Python libraries and frameworks to get you up and started.

Book Description

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.

What you will learn

  • Get familiar with the fundamental concepts and some of the jargons used in the machine learning community
  • Use tools and techniques to mine data from websites
  • Grasp the core concepts of Django framework
  • Get to know the most useful clustering and classification techniques and implement them in Python
  • Acquire all the necessary knowledge to build a web application with Django
  • Successfully build and deploy a movie recommendation system application using the Django framework in Python

Who this book is for

The book is aimed at upcoming and new data scientists who have little experience with machine learning or users who are interested in and are working on developing smart (predictive) web applications. Knowledge of Django would be beneficial. The reader is expected to have a background in Python programming and good knowledge of statistics.

Table of Contents

  1. Introduction to practical machine learning using python
  2. Unsupervised Machine Learning
  3. Machine Learning techniques: supervised learning
  4. Web mining techniques
  5. Recommendation systems
  6. Getting Started with Django
  7. Movie Recommendation System Web Application
  8. Sentiment Analyser application on Movie Reviews
https://github.com/packtpublishing/machine-learning-for-the-web
PDF ISBN: 978-1-78588-872-4
Publisher: Packt Publishing Limited
Copyright owner: © 2016 Packt Publishing Limited
Publication date: 2016
Language: English
Pages: 298
Related subjects:
Computer sciences,
Computer sciences, other

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