Movie Recommendation System using Collaborative Filtering
Learn to create, train and evaluate a recommendation engine with Scikit-Surprise
Learn to clean, analyse and use real-word datasets for recommendation systems
With the amount of available online content ever-increasing and all the platforms trying to grab your attention by giving you personalized recommendations, recommendation engines are more important than ever. In this project-based course, you will create a recommendation system using Collaborative Filtering with help of Scikit-surprise library, which learns from past user behavior. We will be working with a movie lense dataset and by the end of this project, you will be able to give unique movie recommendations for every user based on their past ratings. This project is best suited for anyone who is venturing into data science and is curious as to how recommendation engines work. This project will be a great addition to your portfolio to showcase your real-world hands-on experience with recommendation systems as we would be working with a real-world dataset.
Skills you will develop
Learn step-by-step
In a video that plays in a split-screen with your work area, your instructor will walk you through these steps:
Set up required modules and get them ready for use. Become familiar with the guided project interface
Import real-world dataset and clean it
Do exploratory data analysis on the dataset
Remove the unwanted ratings from the dataset and thus do Dimensionality Reduction
Create trainset and antiset from the data
Train your model on your data and see its performance
Make predictions and recommend the best movies for each user
How Guided Projects work
Your workspace is a cloud desktop right in your browser, no download required
In a split-screen video, your instructor guides you step-by-step
Frequently asked questions
Frequently Asked Questions
What will I get if I purchase a Guided Project?
By purchasing a Guided Project, you'll get everything you need to complete the Guided Project including access to a cloud desktop workspace through your web browser that contains the files and software you need to get started, plus step-by-step video instruction from a subject matter expert.
Are Guided Projects available on desktop and mobile?
Because your workspace contains a cloud desktop that is sized for a laptop or desktop computer, Guided Projects are not available on your mobile device.
Who are the instructors for Guided Projects?
Guided Project instructors are subject matter experts who have experience in the skill, tool or domain of their project and are passionate about sharing their knowledge to impact millions of learners around the world.
Can I download the work from my Guided Project after I complete it?
You can download and keep any of your created files from the Guided Project. To do so, you can use the “File Browser” feature while you are accessing your cloud desktop.
What is the refund policy?
Guided Projects are not eligible for refunds. See our full refund policy.
Is financial aid available?
Financial aid is not available for Guided Projects.
Can I audit a Guided Project and watch the video portion for free?
Auditing is not available for Guided Projects.
How much experience do I need to do this Guided Project?
At the top of the page, you can press on the experience level for this Guided Project to view any knowledge prerequisites. For every level of Guided Project, your instructor will walk you through step-by-step.
Can I complete this Guided Project right through my web browser, instead of installing special software?
Yes, everything you need to complete your Guided Project will be available in a cloud desktop that is available in your browser.
What is the learning experience like with Guided Projects?
You'll learn by doing through completing tasks in a split-screen environment directly in your browser. On the left side of the screen, you'll complete the task in your workspace. On the right side of the screen, you'll watch an instructor walk you through the project, step-by-step.
More questions? Visit the Learner Help Center.
