In this Deploying Machine Learning Models offered by Coursera in partnership with UC San Diego we will learn about Recommender Systems (which we will study for the Capstone project), and also look at deployment issues for data products. By the end of this course, you should be able to implement a working recommender system (e.g. to predict ratings, or generate lists of related products), and you should understand the tools and techniques required to deploy such a working system on real-world, large-scale datasets.
This course is the final course in the Python Data Products for Predictive Analytics Specialization, building on the previous three courses (Basic Data Processing and Visualization, Design Thinking and Predictive Analytics for Data Products, and Meaningful Predictive Modeling). At each step in the specialization, you will gain hands-on experience in data manipulation and building your skills, eventually culminating in a capstone project encompassing all the concepts taught in the specialization.
What you will learn
- Project structure of interactive Python data applications
- Python web server frameworks: (e.g.) Flask, Django, Dash
- Best practices around deploying ML models and monitoring performance
- Deployment scripts, serializing models, APIs
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- Implementing Recommender Systems
- Deploying Recommender Systems
- Recommender System
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- 1 months
Start dates & application deadlines
DisciplinesComputer Sciences Human Computer Interaction Machine Learning View 649 other Short Courses in Computer Sciences in United States
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We are not aware of any academic requirements for this programme.
We are not aware of any English requirements for this programme.
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InternationalFreeTuition FeeBased on the tuition of 0 USD for the full programme during 1 months.
NationalFreeTuition FeeBased on the tuition of 0 USD for the full programme during 1 months.
Coursera provides financial aid to learners who cannot afford the fee. Apply for it by clicking on the Financial Aid link beneath the "Enroll" button on the left. You'll be prompted to complete an application and will be notified if you are approved. You'll need to complete this step for each course in the Specialization, including the Capstone Project.
Studyportals Tip: Students can search online for independent or external scholarships that can help fund their studies. Check the scholarships to see whether you are eligible to apply. Many scholarships are either merit-based or needs-based.
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Apply and win up to €10000 to cover your tuition fees.