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Created by:
Last updated:
September 25, 2023
Duration:
Unlimited Duration
FREE
This course includes:
Unlimited Duration
Badge on Completion
Certificate of completion
Unlimited Duration
Description
CPSC 340: Machine Learning and Data Mining (2012, University of British Columbia). Instructor: Professor Nando de Freitas.
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 Curriculum
- 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
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