Sacred is a tool to help you configure, organize, log and reproduce experiments developed at IDSIA.
- python
- machine-learning
- infrastructure
- reproducible-research
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Sacred is a tool to help you configure, organize, log and reproduce experiments developed at IDSIA.
modular quant framework.
Scalable and user friendly neural :brain: forecasting algorithms.
Deepchecks: Tests for Continuous Validation of ML Models & Data. Deepchecks is a holistic open-source solution for all of your AI & ML validation needs, enabling to thoroughly test your data and models from research to production.
TensorFlowOnSpark brings TensorFlow programs to Apache Spark clusters.
Fast Python Collaborative Filtering for Implicit Feedback Datasets
A python library for self-supervised learning and latent world models on images.
Fast, flexible and easy to use probabilistic modelling in Python.
Seamlessly integrate LLMs into scikit-learn.
Visual tracking library based on PyTorch.
PennyLane is an open-source quantum software platform for quantum computing, quantum machine learning, and quantum chemistry. Create meaningful quantum algorithms, from inspiration to implementation.
Accelerated deep learning R&D
The machine learning toolkit for time series analysis in Python
Visualize and compare datasets, target values and associations, with one line of code.
:sunglasses: A curated list of robotics libraries and software
StellarGraph - Machine Learning on Graphs
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
PyTorch Geometric Temporal: Spatiotemporal Signal Processing with Neural Machine Learning Models (CIKM 2021)
Data manipulation and transformation for audio signal processing, powered by PyTorch
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.
POT : Python Optimal Transport
Multilingual Automatic Speech Recognition with word-level timestamps and confidence
Algorithms for explaining machine learning models
Message Passing Neural Networks for Molecule Property Prediction