pro $24.99 per month
- access to all Manning books, MEAPs, liveVideos, liveProjects, and audiobooks!
- share your subscription with another person
- 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
Look inside
Recommender systems are one of the most popular and lucrative uses of machine learning, allowing businesses and organizations to give personalized suggestions to their customers.
In this liveProject, you’ll use common tools of the Python data ecosystem to design, build, and evaluate a movie recommendation model for the movie website. You’ll kick off your project by building simple genre charts, then work with existing movie rating data to implement personalized recommendations for each customer. When you’ve completed this hands-on and interesting project, you’ll have mastered a cornerstone technique of machine learning that’s in demand across companies and industries.
In this liveProject, you’ll use common tools of the Python data ecosystem to design, build, and evaluate a movie recommendation model for the movie website. You’ll kick off your project by building simple genre charts, then work with existing movie rating data to implement personalized recommendations for each customer. When you’ve completed this hands-on and interesting project, you’ll have mastered a cornerstone technique of machine learning that’s in demand across companies and industries.
This project is designed for learning purposes and is not a complete, production-ready application or solution.
Manning author Kim Falk shares what he likes about the Manning liveProject platform.
book resources
When you start your liveProject, you get full access to the following books for 90 days.
prerequisites
This liveProject is for intermediate Python programmers. To begin this liveProject, you will need to be familiar with:TOOLS
- Basics of NumPy and pandas
- Basics of scikit-learn
- Basics of Matplotlib
- Basics of Jupyter Notebook
- Basics of data science
- Basics of machine learning
you will learn
In this liveProject, you’ll learn to put common Python data science libraries into action to build an in-demand machine learning model.- Data manipulation and analysis using pandas
- Collaborative filtering with negative matrix factorization implemented using scikit-learn
- Produce personalized recommendations using latent vectors created by factorization
- Visualizing the data in the reports using Matplotlib and Seaborn
- Evaluate and optimize algorithm hyperparameters
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 other participants and 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.
choose your plan
pro
monthly
annual
$24.99
$249.99
only $20.83 per month
- share your subscription with one other person
- 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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Build an ML Recommender System project for free
Build an ML Recommender System project for free
team
monthly
annual
$49.99
$499.99
only $41.67 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
-
![]()
Build an ML Recommender System project for free
