Learn Python for data analysis from zero with this tutorial based on Jupyter notebooks.

E-commerce Customer Behaviour Dashboard powered by Streamlit and Plotly

Helpful scripts for board games

Fully-connected feed-forward neural network using TensorFlow 2.x without relying (much) on Keras; trained on MNIST data

Image Classifier using a Convolutional Neural Network implemented with PyTorch Lightning

Multiclass classifier using deep neural networks implemented using PyTorch Lightning

Multiclass classifier using deep neural networks implemented using the Keras API from TensorFlow

Example of a two-sample t-test implemented in Python using SciPy

Example of a two-sample chi-square test implemented in Python

Generate data for sales forecasting

A multi-purpose jet-parton matcher for the ATLAS SUSY RPV multijet search

Convert TFiles into H5 files for the ATLAS SUSY RPV multijet search

Predict extrapolation weights through regression using Keras

Instructions and scripts to find samples of interest to be deleted and to request an extension for them

ML-based multijet background estimation through reweithting

Create Docker images and ymal files to run Kubeflow pipelines to perform inference on background samples for the ATLAS SUSY RPV multijet search

Step by step instructions for deriving extrapolation weights and produce validation plots.

Create docker images for Kubeflow

Evaluate SPANet performance for the ATLAS SUSY RPV multijet search

Example configs for running xAH together CP algorithms

Script only meant to merge ROOT files containing a TTree produced with FactoryTools from dijet samples

Create Docker images and yaml needed to perform a hyperparameter optimization for SPANet with Kubeflow Katib for the ATLAS SUSY RPV multijet search

Simple example of how to train a network to learn to weight data to follow a given probability distribution.