In the Czodrowski lab (www.czodrowskilab.org) group meeting, we started a session "5 Minutes of Fame". Here, we update each other about any sort of (scientific/technological) news that might be of interest to the group.
Date: 2022-08-12
Author: Helge Vatheuer
Description: Simple tasks of rdkit performed with the Copilot plugin inside VSCode - live demo is actually more impressive than the notebook.
Date: 2022-08-05
Author: Son Ha
Description: Quick and convenient way to set up a web interface for you machine learning model.
Date: 2022-07-22
Author: Paul Czodrowski
Description: Quantum mechanics and analytical chemistry courses ported to Jupyter notebooks. One more thing: Blog entry by Derek Lowe
Date: 2022-06-24
Author: Luca Kröll
Description: Short introduction to TikZ package in LaTeX and tikzplotlib tool for Python. Fascilitates making graphs and figures for LaTeX documents.
Date: 2022-06-10
Author: Katharina Alker
Description: This notebook describes how to apply a DecisionTreeClassifier with the implemented algorithm of scikit-learn, which can be found on https://scikit-learn.org/stable/modules/tree.html. Including overtraining plot and visualisation of the important features using the example of morgan fingerprints.
Date: 2022-05-06
Author: Aishvarya Tandon
Description: This notebook introduces you to Cohen's kappa and how to incorporate it with your binary classification model workflow. It's use with k-fold cross-validation and Optuna hyperparameter optimization is also discussed.
Date: 2022-04-29
Author: Helge Vatheuer
Description: Streamlit is a tool to present data interactively, in a web browser - and to make little apps out of it.
Date: 2022-04-08
Author: Son Ha
Description: 1) OpenAI Gym is a collection of Reinforcement Learning environment for you to train your RL algorithm. 2) Academic Phrasebank is a collection of academic sounding phrases you can use for your report/paper.
Date: 2022-03-18
Author: Marcel Baltruschat
Description: This notebook shows how you can do hyperparameter tuning with Optuna and track the results with MLflow. It includes examples for automatic logging together with scikit-learn as well as manual logging with PyTorch.
Date: 2022-03-11
Author: Prof. Dr. Paul Czodrowski
Date: 2022-02-25
Author: Julien Hazemann
Date: 2022-02-18
Author: Frederik Götz
Date: 2022-02-10
Author: Helge Vatheuer
Description: Helpful mixture of linux command line tools and commands
Date: 2022-02-04
Author: Aishvarya Tandon
Description: This notebook introduces you to Optuna and provides cheminformatics examples for its usage.
Date: 2022-01-28
Author: Marcel Baltruschat
Description: This notebook explores PyTorch Captum and GNNExplainer integrated in PyTorch Geometric to make Graph Neural Networks interpretable and more understandable. As an example, a GNN classification model for dividing compounds in two classes according to their mutagenic effect on a bacterium is examined.
Date: 2022-01-21
Author: Son Ha
Description: This Notebook goes through how to construct a simple Graph Neural Network with PyTorch Geometric.
Date: 2021-12-17
Author: Julien Hazemann
Date: 2021-12-17
Author: Julien Hazemann
Date: 2021-11-12
Author: Juliana Gretz
Date: 2021-11-05
Author: Julien Hazemann
Date: 2021-10-08
Author: Juliana Gretz
Date: 2021-09-24
Author: Son Ha
Description: This notebook showcases some implementation of Pyro, a library built on PyTorch to facilitate your need for deep neural network statistical modeling.
Date: 2021-09-02
Author: Prof. Dr. Paul Czodrowski
Date: 2021-08-27
Author: Julien Hazemann
Date: 2021-08-20
Author: Aishvarya Tandon
Description: In this notebook, I compare different dataframe saving and reading techniques, with the focus on parquet. I show that using parquet to save and read big dataframes has advantages over other methods.
Date: 2021-07-23
Author: Helge Vatheuer
Date: 2021-07-16
Author: Marcel Baltruschat
Description: This notebook shows possibilities to speed up cheminformatics using NVIDIA® RAPIDS and Python Multiprocessing. This example includes exploring chemical space, calculating fingerprints, perform clustering or train machine learning models.
Date: 2021-07-09
Author: Prof. Dr. Paul Czodrowski
Date: 2021-02-04
Author: Marcel Baltruschat
Description: This notebook shows a quick summary of some interesting and useful new features introduced in Python 3.8 and 3.9.