Machine Learning Capstone at Coursera Overview
Duration | 19 hours |
Total fee | Free |
Mode of learning | Online |
Difficulty level | Intermediate |
Official Website | Explore Free Course  |
Credential | Certificate |
- Overview
- Highlights
- Course Details
- Curriculum
- Student Reviews
Machine Learning Capstone at Coursera Highlights
- Earn a Certificate upon completion
Machine Learning Capstone at Coursera Course details
- Compare and contrast different machine learning algorithms by creating recommender systems in Python
- Develop a final project using machine learning methods and evaluate your peers' projects
- Predict course ratings by training a neural network and constructing regression and classification models
- Create recommendation systems by applying your knowledge of KNN, PCA, and non-negative matrix collaborative filtering
- In this Machine Learning Capstone course, you will be using various Python-based machine learning libraries such as Pandas, scikit-learn, Tensorflow/Keras
Machine Learning Capstone at Coursera Curriculum
Capstone Overview
Introduction to Machine Learning Capstone
Intro to Recommender Systems
Exploratory Data Analysis and Feature Engineering
Checkpoints: Exploratory Data Analysis on Online Course Enrollment Data
Graded: Exploratory Data Analysis and Feature Engineering
Unsupervised-Learning Based Recommender System
Content-based Recommender Systems
Checkpoints: Unsupervised-Learning Based Recommender System
Graded: Unsupervised-Learning Based Recommendation Systems
Supervised-Learning Based Recommender Systems
Collaborative Filtering-Based Recommender Systems
Checkpoints: Supervised-Learning Based Recommender Systems
Graded: Supervised-Learning Based Recommendation Methods
Share and Present Your Recommender Systems
Elements Of A Successful Data Findings Report
Best Practices For Presenting Your Findings
Final Submission
Congratulations and Next Steps
Credits and Acknowledgements
Other courses offered by Coursera
Student Forum
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