Teaching

Practical labs supporting the lecture on Machine Learning.

Time:

• Group 1:  Thursday,  14:15 - 16:00, room 139 

• Group 2:  Tuesday, 10:15 - 12:00, room 105

Announcements:

• Additional rules for our group: https://docs.google.com/document/d/1DnATA9u9_r2swM7pXu589DmM5FxxCzl_rLgTrbmiFwY/edit?usp=sharing 

• Project topic presentation: 17/19.12.2024

• Project milestone presentation: 14/16.01.2025

Classes:

1. Week 1 (3 & 8.10)

• ml_uwr_23/Assignments/Assignment1.ipynb at master · marekpiotradamczyk/ml_uwr_23 · GitHub -- first list may be similar 

• https://miro.com/app/board/uXjVLXHI3j0=/?share_link_id=206195427182 -- compressed notes from first classes

2. Week 2 (10 & 15.10)

• https://github.com/klaudiabalcer/demos/blob/main/notebooks/EDA.ipynb (data linked in the notebook)

3. Week 3 ()

4. Week 4

5. Week 5 (12 & 14.10)

   • https://www.kaggle.com/datasets/hellbuoy/car-price-prediction/data

   • https://github.com/klaudiabalcer/demos/blob/main/notebooks/linear_regression.ipynb

Example Project Topics:

• [TAKEN] Binary Classification for Credit Card Fraud Detection
  https://www.kaggle.com/datasets/mlg-ulb/creditcardfraud
  https://archive.ics.uci.edu/dataset/144/statlog+german+credit+data

• Community Detection with Spectral Clustering in e-commerce:
  https://paperswithcode.com/task/community-detection
  https://www.kaggle.com/datasets/lokeshparab/amazon-products-dataset

• Matrix Factorization for Movie Recommender Systems:
  https://paperswithcode.com/dataset/movielens,
  https://github.com/gbolmier/funk-svd, https://surpriselib.com/
  comparison to a neural approach like https://arxiv.org/abs/2302.08191

Also held in 2023/24.

The first edition of the project on XAI.

Time: TBA

Announcements:

Example Project Topics:

• https://arxiv.org/abs/2201.06820 - Analyzing the modules in RecEraser

Practical labs supporting the lecture on ADM.

Time: TBA

Announcements:

Practical labs supporting the lecture on Advanced Python Course (2023/24).