Repository Index

Scalable and user friendly neural :brain: forecasting algorithms.

• deep-learning
• forecasting
• esrnn
• nbeats

Java dataframe and visualization library

• dataframe
• data-frame
• java
• java-dataframe

Fast, flexible and easy to use probabilistic modelling in Python.

• python
• machine-learning
• probabilistic-graphical-models
• pytorch

Debugging, monitoring and visualization for Python Machine Learning and Data Science

• ai
• deep-learning
• deeplearning
• machine-learning

The machine learning toolkit for time series analysis in Python

• time-series
• timeseries
• time-series-analysis
• time-series-clustering

Visualize and compare datasets, target values and associations, with one line of code.

• pandas-dataframe
• eda
• pandas
• data-exploration

A well tested and comprehensive Golang statistics library package with no dependencies.

• statistics
• data
• stats
• machine-learning

Deepnote is a drop-in replacement for Jupyter with an AI-first design, sleek UI, new blocks, and native data integrations. Use Python, R, and SQL locally in your favorite IDE, then scale to Deepnote cloud for real-time collaboration, Deepnote agent, and deployable data apps. https://deepnote.com/

• artificial-intelligence
• data
• data-analysis
• data-science

Transform ML models into a native code (Java, C, Python, Go, JavaScript, Visual Basic, C#, R, PowerShell, PHP, Dart, Haskell, Ruby, F#, Rust) with zero dependencies

• machine-learning
• scikit-learn
• statistical-learning
• xgboost

PyTorch Geometric Temporal: Spatiotemporal Signal Processing with Neural Machine Learning Models (CIKM 2021)

• pytorch
• graph-neural-networks
• temporal-networks
• temporal-graphs

A comprehensive set of fairness metrics for datasets and machine learning models, explanations for these metrics, and algorithms to mitigate bias in datasets and models.

• ai
• fairness-ai
• fairness
• fairness-testing

A library for debugging/inspecting machine learning classifiers and explaining their predictions

• scikit-learn
• machine-learning
• xgboost
• lightgbm

Algorithms for outlier, adversarial and drift detection

• anomaly
• outlier
• concept-drift
• detection

Interactive Go programming with Jupyter

• go
• golang
• jupyter-notebook-kernel
• jupyter-notebook

An intuitive library to add plotting functionality to scikit-learn objects.

• scikit-learn
• visualization
• machine-learning
• data-science

Elyra extends JupyterLab with an AI centric approach.

• notebooks
• notebook-jupyter
• jupyterlab
• jupyterlab-extensions

Automatically Visualize any dataset, any size with a single line of code. Created by Ram Seshadri. Collaborators Welcome. Permission Granted upon Request.

• visualization
• python3
• python
• xgboost

Python library for time series forecasting using scikit-learn compatible models, statistical methods, and foundation models

• forecasting
• scikit-learn
• machine-learning
• python

moDel Agnostic Language for Exploration and eXplanation

• machine-learning
• interpretability
• data-science
• xai

Owl - OCaml Scientific Computing @ https://ocaml.xyz

• matrix
• linear-algebra
• ndarray
• statistical-functions

Scalable machine 🤖 learning for time series forecasting.

• forecast
• forecasting
• machine-learning
• lightgbm

DataFrames for Go: For statistics, machine-learning, and data manipulation/exploration

• golang
• go
• data-science
• machine-learning

[CONTRIBUTORS WELCOME] Generalized Additive Models in Python

• machine-learning
• data-science
• scientific-computing
• python

Python package for graph statistics

• graph
• data-science
• networks
• python