Machine learning

CHATGPT : Rédiger le PROMPT PARFAIT (Tuto Prompt Engineering)

CHATGPT: Writing the PERFECT PROMPT (Prompt Engineering Tutorial)

Spring 2023 6.8210 Lecture 6: Dynamic Programming III

6.8210 Spring 2023 Lecture 3 Part 2

Constrained Reinforcement Learning for Robotics via Scenario-Based Programming

Soft Boundary K-Means Clustering

Semi-Supervised Regression

Mixture Distributions

Machine Learning Practice: Conclusions

Learning Gaussian Mixture Distributions

Label Spreading

Label Propagation

K-Means Clustering: Example in Scikit-Learn

K-Means Clustering

Expectation Maximization Learning Example

Fall 2022 6.4210/2 Lecture 19: Intuitive physics (part 1)

Inject Yourself into the AI and Make Any Image With Your Face! (100% FREE Method)

Fall 2022 6.4210/2 Lecture 18: Reinforcement learning (part 1)

t-Statistic Neighbor Embedding

T-SNE: Example in Scikit-Learn

Principal Component Analysis: Example in Scikit-Learn

Principal Component Analysis with Kinematics: Example in Scikit-Learn

Principal Component Analysis

Multidimensional Scaling

Locally Linear Embeddings: Example 2

Locally Linear Embedding: Example 1

Locally Linear Embedding

Kernel Principal Component Analysis and Kinematics: Example in Scikit-Learn

Introduction to Dimensionality Reduction

Embedding-Based Methods for Dimensionality Reduction

Regression Trees

Random Forests

Probability Tree Learning

Introduction to Decision Trees

Gradient Boosting

Feature Importance

Example: Regression Trees

Example: Probability Tree Learning

Example: Implementing a Voting Classifier

Example: Implementing a Bagging Classifier

Example: Gradient Boosting