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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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