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Manning – Building a Recommendation System With Surprise and Fast Ai

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Manning – Building a Recommendation System With Surprise and Fast Ai-iLLiTERATE
English | Size: 435.39 MB
Category: Tutorial

Ariel Gamino shows how to put collaborative filtering techniques into action to create recommendation engines, one of the most useful types of machine learning application. [Read more…]

Packt – Building Recommendation Systems with Python

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Packt – Building Recommendation Systems with Python
English | Size: 593.52 MB
Category: CBTs


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. [Read more…]

Packt Building Recommendation Systems With Python

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Packt Building Recommendation Systems With Python-JGTiSO
English | Size: 357.47 MB
Category: Tutorial


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
[Read more…]

O’Reilly – Recommendation System

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O’Reilly – Recommendation System
English | Size: 327.51 MB
Category: Tutorial


Recommendation systems are a class of machine learning models with many applications. The idea behind recommendation systems is simple: filtering information to suggest items (anything from clothes to films) to users with the predicted probability that the users will enjoy such items. This course provides an introduction to recommendation systems. It starts by looking at the applications for these systems with a focus on the big companies whose fortune is built upon them. It then goes through a discussion of the different types of recommendation systems and how to implement them. You’ll explore non-personalized systems, association rule learning, collaborative filtering, personalized systems, and the methods used to assess the quality (i.e., how good are the recommendations?) of a recommendation system. Learners should understand basic logic, supervised learning, and statistics. [Read more…]

Total Training – Machine Learning – Recommendation Systems in Python

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Total Training – Machine Learning – Recommendation Systems in Python
English | Size: 0.99 GB
Category: CBTs


Understand How Online Recommendations Work by Building a Movie App. In this Recommendation Systems in Python online course, you will learn about key concepts such as content-based filtering, collaborative filtering, neighborhood models, matrix factorization, and more! By the time you have finished the training, you will be able to build a movie recommendation system in Python by mastering both theory and practice. Recommendation Engines perform a variety of tasks, but the most important one is to find products that are most relevant to the user. [Read more…]