/EP_23_Intro_to_ML_Workshop

Primary LanguageJupyter NotebookMIT LicenseMIT

EuroPython 23

Intro to ML Workshop

https://ep2023.europython.eu/wai

Introduction to Machine Learning (Talk)

  • What is Machine Learning?
  • What is the ML-AI ecosystem?
  • Types of Machine Learning techniques
  • Real-world Applications of Machine Learning

The Philosophy Behind Machine Learning (Talk and Hands-on)

  • Training, Validation, and Loss
  • Concept of (Stochastic) Gradient Descent and Learning Rate
  • Concept of Generalization & Cross-Validation
  • Problems with Underfitting or Overfitting

Introduction to ScikitLearn as a Python Library for ML

ML Workflow Overview

  • Data Cleaning & Preparation
  • Data Splitting
  • Feature Engineering

Implementing a Regressor using Scikit Learn

  • Linear Regression
  • Evaluation Techniques for Regression

Implementing a Classifier using Scikit Learn

  • Data Cleaning & Preparation
  • Feature Engineering
  • Logistic Regression and Decision Trees
  • Evaluation Techniques for Classification

Conclusion