Four-Project Series
- prerequisites
- intermediate Python • basics of NumPy, pandas, scikit-learn • basics of machine learning
- skills learned
- read, process, and exploit user-item data • define and compute similarities between users and items using interactions • compute similarities between users and items in a recommender system
pro $24.99 per month
- access to all Manning books, MEAPs, liveVideos, liveProjects, and audiobooks!
- choose one free eBook per month to keep
- exclusive 50% discount on all purchases
lite $19.99 per month
- access to all Manning books, including MEAPs!
team
5, 10 or 20 seats+ for your team - learn more
In this series of liveProjects, you’ll complete all the steps to build a recommendation system for a movie streaming website. Your system will need to learn the tastes of its users and predict which movies they might want to watch. You’ll work with movie data points like names, genres, and directors, and mapped interactions such as ratings and tags.
These projects are designed for learning purposes and are not complete, production-ready applications or solutions.
here's what's included
Project 1 Collaborative Similarities
In this liveProject, you’ll build a movie recommendation system based on movies that your users have previously interacted with. This system is designed to boost engagement and keep your users on your site. You’ll develop a competitive array of similarity functions, and create your own recommender system based on these similarities. Finally, you’ll evaluate your system’s effectiveness and tune its parameters.
Project 2 Content-Based Similarities
In this liveProject, you’ll build a movie recommendation system based on the content and metadata of movies in your system. This system is intended to maximize the satisfaction of your movie-watching users. You’ll start with an analysis to determine the content of your movies, then use that data to implement content-based similarities for both products and users. You’ll build and evaluate your recommender system based on these connections, till it’s the best it can be!
Project 3 Dimensionality Reduction
In this liveProject, you’ll build a movie recommendation system that reduces the dimensionality of the spaces involved to enhance its performance so that latent representations are identified, which aim to capture users and items interactions with the system on the same latent vector space. You’ll work to compute clusters on the movies and clients of your site, and utilize latent representations of users and items with a reduced dimensionality to compute similarities. Once you’ve established this data, you’ll build and test your recommendation engine.
Project 4 Learning Similarities
In this liveProject, you’ll determine what similarities there are between certain movies, and then build a recommendation system based on the similarities you’ve identified. Although you’ll be working with movie data for a streaming website, identifying similarities can help enhance recommendation engines for any item or product. You’ll develop a general technique for spotting similarities, then apply your learned similarities to build a recommendation engine. You’ll then enrich your model with collaborative and content-based data, and evaluate and compare your model.
books resources
When you start each of the projects in this series, you'll get full access to the following books for 90 days.
choose your plan
pro
monthly
annual
$24.99
$249.99
only $20.83 per month
- access to all Manning books, MEAPs, liveVideos, liveProjects, and audiobooks!
- choose another free product every time you renew
- choose twelve free products per year
- exclusive 50% discount on all purchases
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Similarities and Recommender Systems project for free
Similarities and Recommender Systems project for free
team
monthly
annual
$49.99
$399.99
only $33.33 per month
- five seats for your team
- access to all Manning books, MEAPs, liveVideos, liveProjects, and audiobooks!
- choose another free product every time you renew
- choose twelve free products per year
- exclusive 50% discount on all purchases
-
![]()
Similarities and Recommender Systems project for free
Prerequisites
The liveProject is for intermediate Python programmers who know the basics of data science. To begin this liveProject, you will need to be familiar with the following:
TOOLS
- Intermediate Python, min. version 3.6.0
- Basics of data structures
- Basics of NumPy, min. version 1.19.0
- Basics of pandas, min. version 1.1.0
- Basics of scikit-learn, min. version 0.20.3
- Basics of Jupyter Notebook
features
- Self-paced
- You choose the schedule and decide how much time to invest as you build your project.
- Project roadmap
- Each project is divided into several achievable steps.
- Get Help
- While within the liveProject platform, get help from fellow participants and even more help with paid sessions with our expert mentors.
- Compare with others
- For each step, compare your deliverable to the solutions by the author and other participants.
- book resources
- Get full access to select books for 90 days. Permanent access to excerpts from Manning products are also included, as well as references to other resources.
