Machine Learning FUN - Module 3 & 4

Machine Learning FUN

In this study group, we will be working through the "Machine learning in Python with scikit-learn" course by France Université Numérique: https://www.fun-mooc.fr/en/courses/machine-learning-python-scikit-learn/

This meetup is free and open to all.

Over the next 8 weeks, we will be following the online FUN course weekly.

The first meeting will be on Wednesday 19 May at 20:00. Next on Thursdays from 20:00 to 21:00, online via Hackerspace Trójmiasto Discord (https://discord.gg/AeUGR9m)

Each session we will use that week’s lectures and course materials as a basis for discussion and learning. Everyone is invited to contribute their insights and questions.

Before each session, watch the lecture for that week and work on course assignments.

To get access to course materials enroll via the course website (free).

In this course we will learn:

Fundamental concepts of machine learning

Build a predictive modeling pipeline with scikit-learn

Develop intuitions behind machine learning models from linear models to gradient-boosted decision trees

Evaluate the statistical performance of your models

Course plan:

Introduction

Module 1. The Predictive Modeling Pipeline

Module 2. Selecting the best model

Module 3. Hyperparameters tuning

Module 4. Linear Models

Module 5. Decision tree models

Module 6. Ensemble of models

Module 7. Evaluating model performance

Expect to spend about 4 hours per week on your own time (i.e. to watch the video and run the homework programs)

Prerequisites:

The course aims to be accessible without a strong technical background. The requirements for this course are:

- basic knowledge of Python programming: defining variables, writing functions, importing modules

- some prior experience with the NumPy, pandas, and Matplotlib libraries is recommended but not required

For a quick introduction to these libraries, you can use the following resources: Introduction to NumPy and Matplotlib by Sebastian Raschka (https://sebastianraschka.com/blog/2020/numpy-intro.html) and 10 minutes to pandas (https://pandas.pydata.org/pandas-docs/stable/user_guide/10min.html).

Please note that we have no official connection with FUN.

Hope to see you there,

Hackerspace Trójmiasto