Introduction to Machine Learning

this repo contains all the material for lectures about "introduction to machine learning and dimensionality reduction" ( course for humanists and linguists)

---

This course is divided in 2 Days :

• Day1 :

  • Introduction to supervised and unsupervised machine learning

  • How setup python / git environment

  • Introduction to Statistical Analysis

    • Tests and Assumptions
    • EDA
    • Pre-processing and Encoding

  • Introduction to Linear Regression

    • traning, inference, evaluation
    • metrics for LR

  • Hands-On Tutorial on different datasets

• Day2 :

  • Introduction to Classification
  • Logistic Regression
    • Confusion Matrix
    • Metrics ( Acc, TPr, TNr, Precision, F1 score, ROC )
  • Multinominal Logistic Regression
    • hands-on Soft-max function
  • Soft introduction to Decision Trees family
  • Brief introduction to Cluster Analysis
    • K-Means Example
      • metrics, evaluation, plot
  • Hands-On Tutorial
    • from data to supervised problem
    • develop target variable
    • evaluate different models and compare based on metrics