Contenu

• C1: Machine learning

  • Trailer

  • Intro to Data Co-Lab

  • Intro to ML

  • Supervised Learning

  • Unsupervised Learning

  • Weather Forecasting

  • Weather Forecasting: Normal Distribution

  • Weather Forecasting: Synthetic Data

  • Python example : Weather Forecasting 1

  • Weather Forecasting: OverSampling and Undersampling

  • Weather Forecasting: Regression

  • Weather Forecasting: Classification

  • Weather Forecasting: KNN

  • Python example : Weather Forecasting 2

  • Naive Bayes

  • Naive Bayes example

  • Pros and Cons Naive Bayes

  • Naive Bayes Example Python

  • Decision Tree

  • Building a Decision Tree

  • Building a Decision Tree part 2

  • Another Decision Tree algorithm

  • Decision Tree: Random Forest

  • Apriori

  • Apriori Pros and Cons

  • Python Example: Apriori

  • Topic Modeling Intro

  • Topic Modeling: Part 1

  • Topic Modeling: Preprocessing

  • Topic Modeling: TF-IDF

  • Topic Modeling: TF-IDF 2

  • Topic Modeling: Dimensionality Reduction

  • Topic Modeling: K-Means

  • Topic Modeling: LDA

  • Topic Modeling: LDA part 2

  • Pyhon example : Topic Modeling 1

  • Python example : Topic Modeling 2