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CPSC 340: Machine Learning and Data Mining (2012, University of British Columbia). Instructor: Professor Nando de Freitas.
FREE
This course includes
Hours of videos
888 years, 9 months
Units & Quizzes
32
Unlimited Lifetime access
Access on mobile app
Certificate of Completion
This course will provide an introduction to machine learning and data mining. It will teach the basic principles and skills required for analysing data in a principled way: finding statistical patterns, dimensionality reduction, clustering, classification and prediction. Students will also have the opportunity of learning Python, a widely used programming language.
Course Currilcum
- Lecture 01 – Introduction to Machine Learning Unlimited
- Lecture 02 – Introduction to Machine Learning 2 Unlimited
- Lecture 03 – Basic Probability Unlimited
- Lecture 04 – Introduction to Probability, Linear Algebra and Pagerank Unlimited
- Lecture 05 – Introduction to Bayes Rule Unlimited
- Lecture 06 – Bayes Rule and Bayesian Networks Unlimited
- Lecture 07 – Bayesian Networks, Probabilistic Graphical Models Unlimited
- Lecture 08 – Inference in Bayesian Networks and Dynamic Programming Unlimited
- Lecture 09 – Hidden Markov Models (HMMs) Unlimited
- Lecture 10 – Expectation, Probability and Bernoulli Models Unlimited
- Lecture 11 – Maximum Likelihood Unlimited
- Lecture 12 – Bayesian Learning Unlimited
- Lecture 13 – Learning Bayesian Networks Unlimited
- Lecture 14 – Linear Algebra Revision for Machine Learning and Web Search Unlimited
- Lecture 15 – Singular Value Decomposition (SVD) Unlimited
- Lecture 16 – Principal Component Analysis (PCA) Unlimited
- Lecture 17 – Linear Prediction Unlimited
- Lecture 18 – Least Squares and the Multivariate Gaussian Unlimited
- Lecture 20 – Cross-validation, Big Data and Regularization Unlimited
- Lecture 21 – L1 Regularization and the Lasso Unlimited
- Lecture 22 – Sparse Models and Variable Selection Unlimited
- Lecture 23 – Dirichlet and Categorical Distributions Unlimited
- Lecture 24 – Text Classification with Naive Bayes Unlimited
- Lecture 25 – Twitter Sentiment Prediction with Naive Bayes Unlimited
- Lecture 26 – Optimization Unlimited
- Lecture 27 – Logistic Regression Unlimited
- Lecture 28 – Neural Networks Unlimited
- Lecture 29 – Neural Nets and Backpropagation Unlimited
- Lecture 30 – Deep Learning Unlimited
- Lecture 31 – Decision Trees Unlimited
- Lecture 32 – Random Forests Unlimited
- Lecture 33 – Random Forests, Face Detection and Kinect Unlimited
