In this self-paced online course you will learn how to build a movie recommendation system. You will learn the fundamentals of machine learning algorithm, principal component analysis and regularization. Using training data, you will learn how to train algorithms to predict the outcome for future data-sets. Some of the common uses of machine learning is speech recognition, visual search implemented by Google and Amazon, chat bots and service recommendation systems.
What You'll Learn
- The basics of machine learning
- How to perform cross-validation to avoid 'overtraining'
- Several popular machine learning algorithms
- How to build a movie recommendation system
- What is regularization and why it is useful?
Anyone can enroll in this course. No prior data science or machine learning knowledge is required.
This course has 7-sections.
- Welcome to Data Science: Machine Learning!
- Important Pre-Course Survey
- Introduction to Machine Learning Overview
- 1.1: Introduction to Machine Learning
- Machine Learning Basics Overview
- 2.1: Basics of Evaluating Machine Learning Algorithms
- 2.2: Conditional Probabilities
- Linear Regression for Prediction, Smoothing, and Working with Matrices Overview
- 3.1: Linear Regression for Prediction
- 3.2: Smoothing
- 3.3: Working with Matrices
- Distance, Knn, Cross-validation, and Generative Models Overview
- 4.1: Nearest Neighbors
- 4.2: Cross-validation
- 4.3: Generative Models
- Classification with More than Two Classes and the Caret Package Overview
- 5.1: Classification with More than Two Classes
- 5.2: Caret Package
- 5.3: Titanic Exercises
- Model Fitting and Recommendation Systems Overview
- 6.1: Case Study: MNIST
- 6.2: Recommendation Systems
- 6.3: Regularization
- 7.1 Final Assessment: Breast Cancer Prediction Project (Verified Learners only)
- 7.2: Course Wrap-up
- Online. Self-paced
- 8 Weeks. 2-4 hrs p/week
- Level: Introductory
- Language: English
- Videos: Yes
- Price: FREE
Course developed by
Harvard University (HarvardX)
Harvard University is a private Ivy League research university in Cambridge, Massachusetts, with about 6,700 undergraduate students and about 13,100 postgraduate students. Harvard is the United States' oldest institution of higher learning. Its history, influence, wealth, and academic reputation have made it one of the most prestigious universities in the world.
Prof. Rafael Irizarry
Professor of Biostatistics at Harvard University
Rafael Irizarry is a Professor of Biostatistics at the Harvard T.H. Chan School of Public Health and a Professor of Biostatistics and Computational Biology at the Dana Farber Cancer Institute. For the past 15 years, Dr. Irizarry’s research has focused on the analysis of genomics data. During this time, he has also has taught several classes, all related to applied statistics. Dr. Irizarry is one of the founders of the Bioconductor Project, an open source and open development software project for the analysis of genomic data. His publications related to these topics have been highly cited and his software implementations widely downloaded.
NOTE: Blockchain Academy Plt. is in partnership with Harvard University via edX. Enrolling into the course is free. However, if you decide to upgrade, we may receive a commission from the university.