Lab course materials for IEMBA 8/9 course "Coding and Artificial Intelligence"

Overview

IEMBA 8/9 - Coding and Artificial Intelligence

Course Banner

Dear IEMBA 8/9 students,

welcome to our IEMBA 8/9 elective course Coding and Artificial Intelligence, taught by Prof. Dr. Damian Borth and Prof. Dr. Barbara Weber. In this course, lectures and hands-on lab courses alternate to provide a better learning experience. Lab course materials for Python programming, Machine Learning und Deep Learning are available in and accessible through this repository.

Please use a laptop computer for the lab courses (not a tablet) to be able to fully participate in the exercises.

Happy Coding!

Your IEMBA teaching team


This table lists all coding lab notebooks and exercise notebooks:

Date Topic Lab Notebook Exercise Notebook Solution Notebook
< Mon, Jan 17 Prerequisite - Binder
Open In Colab
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Mon, Jan 17 Python 101: Jupyter Notebooks and Python Basics Binder
Open In Colab
Binder
Open In Colab
Binder
Open In Colab
Tue, Jan 18, morning session Python 102: Numerical Math & Images Binder
Open In Colab
Binder
Open In Colab
Binder
Open In Colab
Tue, Jan 18, afternoon session Machine Learning I
(Naive Bayes)
Binder
Open In Colab
Binder
Open In Colab
Binder
Open In Colab
Tue, Jan 18, afternoon session Machine Learning II
(k Nearest-Neighbors)
Binder
Open In Colab
Binder
Open In Colab
Binder
Open In Colab
Wed, Jan 19, morning session Deep Learning I
(Artificial Neural Nets)
Binder
Open In Colab
Binder
Open In Colab
Binder
Open In Colab
Wed, Jan 19, afternoon session Deep Learning II
(Convolutional Neural Nets)
Binder
Open In Colab
Binder
Open In Colab
Binder
Open In Colab
< TBD Exam Exercise - Binder
Open In Colab
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Owner
Artificial Intelligence & Machine Learning (AI:ML Lab) @ HSG
Deep Learning Research by AIML Team @ HSG
Artificial Intelligence & Machine Learning (AI:ML Lab) @ HSG
A program to recognize fruits on pictures or videos using yolov5

Yolov5 Fruits Detector Requirements Either Linux or Windows. We recommend Linux for better performance. Python 3.6+ and PyTorch 1.7+. Installation To

Fateme Zamanian 30 Jan 06, 2023
Implementation of Shape and Electrostatic similarity metric in deepFMPO.

DeepFMPO v3D Code accompanying the paper "On the value of using 3D-shape and electrostatic similarities in deep generative methods". The paper can be

34 Nov 28, 2022
A Convolutional Transformer for Keyword Spotting

☢️ Audiomer ☢️ Audiomer: A Convolutional Transformer for Keyword Spotting [ arXiv ] [ Previous SOTA ] [ Model Architecture ] Results on SpeechCommands

49 Jan 27, 2022
Official and maintained implementation of the paper "OSS-Net: Memory Efficient High Resolution Semantic Segmentation of 3D Medical Data" [BMVC 2021].

OSS-Net: Memory Efficient High Resolution Semantic Segmentation of 3D Medical Data Christoph Reich, Tim Prangemeier, Özdemir Cetin & Heinz Koeppl | Pr

Christoph Reich 23 Sep 21, 2022
1st place solution to the Satellite Image Change Detection Challenge hosted by SenseTime

1st place solution to the Satellite Image Change Detection Challenge hosted by SenseTime

Lihe Yang 209 Jan 01, 2023
An implementation of a sequence to sequence neural network using an encoder-decoder

Keras implementation of a sequence to sequence model for time series prediction using an encoder-decoder architecture. I created this post to share a

Luke Tonin 195 Dec 17, 2022
🛰️ List of earth observation companies and job sites

Earth Observation Companies & Jobs source Portals & Jobs Geospatial Geospatial jobs newsletter: ~biweekly newsletter with geospatial jobs by Ali Ahmad

Dahn 64 Dec 27, 2022
Streamlit App For Product Analysis - Streamlit App For Product Analysis

Streamlit_App_For_Product_Analysis Здравствуйте! Перед вами дашборд, позволяющий

Grigory Sirotkin 1 Jan 10, 2022
Pytorch implementation of FlowNet by Dosovitskiy et al.

FlowNetPytorch Pytorch implementation of FlowNet by Dosovitskiy et al. This repository is a torch implementation of FlowNet, by Alexey Dosovitskiy et

Clément Pinard 762 Jan 02, 2023
Cancer metastasis detection with neural conditional random field (NCRF)

NCRF Prerequisites Data Whole slide images Annotations Patch images Model Training Testing Tissue mask Probability map Tumor localization FROC evaluat

Baidu Research 731 Jan 01, 2023
Benchmarks for the Optimal Power Flow Problem

Power Grid Lib - Optimal Power Flow This benchmark library is curated and maintained by the IEEE PES Task Force on Benchmarks for Validation of Emergi

A Library of IEEE PES Power Grid Benchmarks 207 Dec 08, 2022
Gesture-Volume-Control - This Python program can adjust the system's volume by using hand gestures

Gesture-Volume-Control This Python program can adjust the system's volume by usi

VatsalAryanBhatanagar 1 Dec 30, 2021
Implementation of Uformer, Attention-based Unet, in Pytorch

Uformer - Pytorch Implementation of Uformer, Attention-based Unet, in Pytorch. It will only offer the concat-cross-skip connection. This repository wi

Phil Wang 72 Dec 19, 2022
Kaggle Lyft Motion Prediction for Autonomous Vehicles 4th place solution

Lyft Motion Prediction for Autonomous Vehicles Code for the 4th place solution of Lyft Motion Prediction for Autonomous Vehicles on Kaggle. Discussion

44 Jun 27, 2022
This repository consists of Blender python scripts and corresponding assets to generate variants of the CANDLE dataset

candle-simulator This repository consists of Blender python scripts and corresponding assets to generate variants of the IITH-CANDLE dataset. The rend

1 Dec 15, 2021
Deepfake Scanner by Deepware.

Deepware Scanner (CLI) This repository contains the command-line deepfake scanner tool with the pre-trained models that are currently used at deepware

deepware 110 Jan 02, 2023
Awesome Deep Graph Clustering is a collection of SOTA, novel deep graph clustering methods

ADGC: Awesome Deep Graph Clustering ADGC is a collection of state-of-the-art (SOTA), novel deep graph clustering methods (papers, codes and datasets).

yueliu1999 297 Dec 27, 2022
A tutorial showing how to train, convert, and run TensorFlow Lite object detection models on Android devices, the Raspberry Pi, and more!

A tutorial showing how to train, convert, and run TensorFlow Lite object detection models on Android devices, the Raspberry Pi, and more!

Evan 1.3k Jan 02, 2023
NeuroLKH: Combining Deep Learning Model with Lin-Kernighan-Helsgaun Heuristic for Solving the Traveling Salesman Problem

NeuroLKH: Combining Deep Learning Model with Lin-Kernighan-Helsgaun Heuristic for Solving the Traveling Salesman Problem Liang Xin, Wen Song, Zhiguang

xinliangedu 33 Dec 27, 2022
Einshape: DSL-based reshaping library for JAX and other frameworks.

Einshape: DSL-based reshaping library for JAX and other frameworks. The jnp.einsum op provides a DSL-based unified interface to matmul and tensordot o

DeepMind 62 Nov 30, 2022