By : Eric Rodríguez
Released : 30 May 2019 (New Release!)
Torrent Contains : 32 Files, 7 Folders
Course Source : https://www.packtpub.com/big-data-and-business-intelligence/building-recommendation-systems-python-video
Build real-world recommendation systems using collaborative, content-based, and hybrid filtering techniques in Python
Video Details
ISBN 9781788991704
Course Length 1 hour 35 minutes
Table of Contents
• Get Started with Text Mining and Cleaning Data
• Collaborative Filtering-Based Recommender System
• Content and Popularity Based Recommender Systems
• Hybrid Recommender System
• Flask Web Application Using PyCharm
Learn
• Build your own recommendation engine with Python to analyze data
• Use effective text-mining tools to get the best raw data
• Master collaborative filtering techniques based on user profiles and the item they want
• Content-based filtering techniques that use user data such as comments and ratings
• Hybrid filtering technique which combines both collaborative and content-based filtering
• Utilize Pandas and sci-kit-learn easy-to-use data structures for data analysis
About
Recommendation Engines have become an integral part of any application. For accurate recommendations, you require user information. The more data you feed to your engine, the more output it can generate – for example, a movie recommendation based on its rating, a YouTube video recommendation to a viewer, or recommending a product to a shopper online.
In this practical course, you will be building three powerful real-world recommendation engines using three different filtering techniques. You'll start by creating usable data from your data source and implementing the best data filtering techniques for recommendations. Then you will use Machine Learning techniques to create your own algorithm, which will predict and recommend accurate data.
By the end of the course, you'll be able to build effective online recommendation engines with Machine Learning and Python – on your own.
The code bundle for this video course is available at - https://github.com/PacktPublishing/Building-Recommendation-Systems-with-Python
Style and Approach
This course is a step-by-step guide to building your own recommendation engine with Python. It will help you gain all the training and skills you need to make suggestions as to data that a website user might be interested in, by using various data filtering techniques.
Features:
• Understand how to work with real data using a recommendation in Python
• Graphical representation of categories or classes to visualize your data
• Comparison of different recommender systems and learning to help you choose the right one
Author
Eric Rodríguez
Eric Rodríguez is a mechatronics engineer with an interest in the areas of machine learning and robotics. His passion for programming began around 5 years ago when he started learning how to build web applications. He moved on to develop Android applications and finally completed his Master's degree in Computer Science. He has also started using C# in Xamarin to develop mobile applications. Eric has years of practical experience in the software development industry as a software engineer.
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