This repository contains datasets and colab links to be used in Workshop 2023 Winter Semster.
Day 1 18.09 Introduction to Machine learning, deep learning, google colab, and other libraries. Through this notebook, we can introduce basic libraries for Image, text, and audio manipulation. The goal of this Notebook is to introduce different data modalities and show students which common libraries are there for manipulating specific types of data. Link: https://colab.research.google.com/drive/19QbX2MRFwHKDMdBxi1sezo63MKmPgKQM?usp=sharing
Day 2: 19.09 Object detection introduction with Images. An Introduction to Single-stage Object Detection Networks in which we will create a simple YOLOv5 model on chessboard images of a single class and then perform Inference. This notebook is built in a way that students can then replace and Label their own images and generate simple object detection models. For data labeling, we will introduce the Web-API from makesense.ai Link: https://colab.research.google.com/drive/1w_7GeONCKQoteaWXWU7hMNEKgRg7m3sV?usp=sharing
Day 3: 20.09 Time series forecasting with weather dataset from Montenegro (Podgorica weather data from 2014-2022). Introduction to N-beats, RNN, and LSTM models and comparison of these models as single uni-variate temperature forecasting models. Link: https://colab.research.google.com/drive/1UB-TtjmKNCI13Ph2m8xuAhoUGo8PH4wT?usp=sharing
Day 4: 21.09 Explained AI (e.g., SHAP, GradCAM). This notebook introduces the concepts of explainability of machine learning models. There are several levels of concepts that can be explained using a series of several sub-colab notebooks that we will use depending on the Interest of the students will use. Link: https://drive.google.com/file/d/1M5r2EzO0r_0hreE6m3-VQfVUXmhJoc90/view?usp=sharing
Some content used in the described workshops has been taken from the Q-AMeLiA project (q-amelia.in.hs-furtwangen.de/).
