Artificial Neural Networks / Python

Claude Code skills that turn any codebase into an interactive knowledge graph you can explore, search, and ask questions about (Multi-platform e.g., Codex are supported).

Chronos: Pretrained Models for Time Series Forecasting

A logical, reasonably standardized, but flexible project structure for doing and sharing data science work.

EnergyPlus™ is a whole building energy simulation program that engineers, architects, and researchers use to model both energy consumption and water use in buildings.

Ulysses-HIRS: A Hybrid Information Retrieval System for Legislative Documents

Generate Diverse Counterfactual Explanations for any machine learning model.

Minerva is a framework for training machine learning models for researchers.

A PyTorch implementation for the paper FedSiam: Towards Adaptive Federated Semi-Supervised Learning https://arxiv.org/abs/2012.03292 .

Mastering the Lightning Network (LN)

Mastering Ethereum: 2nd Edition, by Andreas M. Antonopoulos, Gavin Wood, Carlo Parisi, Alessandro Mazza, Niccolò Pozzolini

Mastering Bitcoin 3rd Edition - Programming the Open Blockchain

Repositório

(WWW'21) ATON - an Outlier Interpreation / Outlier explanation method

ELKI Example Project

ELKI Data Mining Toolkit

A scikit-learn compatible library for anomaly detection

Model explainability that works seamlessly with 🤗 transformers. Explain your transformers model in just 2 lines of code.

The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.

Source code of $\beta^3$-IRT(https://arxiv.org/abs/1903.04016)

Spark implementation of k-medoids clustering algorithm

Python implementations of the k-modes and k-prototypes clustering algorithms, for clustering categorical data

Movie review dataset Word2Vec & sentiment classification Zeppelin notebook