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Book Overview & Buying
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Table Of Contents
Machine Learning for the Web
By :
Machine Learning for the Web
By:
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)
Preface
1. Introduction to Practical Machine Learning Using Python
2. Unsupervised Machine Learning
3. Supervised Machine Learning
4. Web Mining Techniques
5. Recommendation Systems
6. Getting Started with Django
7. Movie Recommendation System Web Application
8. Sentiment Analyser Application for Movie Reviews
Index


