Lesson 1
Free
Machine Learning
Course
In this course, you'll learn how to apply Supervised, Unsupervised and Reinforcement Learning techniques for solving a range of data science problems.
In this course, you'll learn how to apply Supervised, Unsupervised and Reinforcement Learning techniques for solving a range of data science problems.
Last Updated March 4, 2022
No experience required
Course Lessons
Lesson 2
SL 1 - Decision Trees
Lesson 3
SL 2 - Regression & Classification
Lesson 4
SL 3 - Neural Networks
Lesson 5
SL 4 - Instance Based Learning
Lesson 6
SL 5 - Ensemble B&B
Lesson 7
SL 6 - Kernel Methods & SVMs
Lesson 8
SL 7 - Comp Learning Theory
Lesson 9
SL 8 - VC Dimensions
Lesson 10
SL 9 - Bayesian Learning
Lesson 11
SL 10 - Bayesian Inference
Lesson 12
UL 1 - Randomized Optimization
Lesson 13
UL 2 - Clustering
Lesson 14
UL 3 - Feature Selection
Lesson 15
UL 4 - Feature Transformation
Lesson 16
UL 5 - Info Theory
Lesson 17
RL 1 - Markov Decision Processes
Lesson 18
RL 2 - Reinforcement Learning
Lesson 19
RL 3 - Game Theory
Lesson 20
RL 4 - Game Theory Continued
Lesson 21
Outro
Taught By The Best
Michael Littman
Instructor
Charles Isbell
Instructor
Pushkar Kolhe
Instructor
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