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Unified Training of Universal Time Series Forecasting Transformers
A Python library that helps data scientists to infer causation rather than observing correlation.
An open-access benchmark and toolbox for electricity price forecasting
Kedro is a toolbox for production-ready data science. It uses software engineering best practices to help you create data engineering and data science pipelines that are reproducible, maintainable,…
The Incredible PyTorch: a curated list of tutorials, papers, projects, communities and more relating to PyTorch.
Automatic extraction of relevant features from time series:
A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning
Tensors and Dynamic neural networks in Python with strong GPU acceleration
An Agnostic Computer Vision Framework - Pluggable to any Training Library: Fastai, Pytorch-Lightning with more to come
Make Your Company Data Driven. Connect to any data source, easily visualize, dashboard and share your data.
Fast and flexible physics-based battery models in Python
Examples of PyMC models, including a library of Jupyter notebooks.
Resources for "Introduction to Deep Learning" course.
Tutorial for OR-Tools training
Evidently is an open-source ML and LLM observability framework. Evaluate, test, and monitor any AI-powered system or data pipeline. From tabular data to Gen AI. 100+ metrics.
Bayesian Optimization algorithms with various recent improvements
Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
A simple and extensible library to create Bayesian Neural Network layers on PyTorch.
Easily work with deeply nested dictionaries and write clean code using FlexDict; a small subclass of dict. FlexDict provides automatic and arbitrary levels of nesting along with additional utility …
A statistical library designed to fill the void in Python's time series analysis capabilities, including the equivalent of R's auto.arima function.
Statistical Rethinking course in pymc3
Statistical Rethinking course and book package
Bayesian models to compute performance and uncertainty of returns and alpha.
Course 5SSD0 - Bayesian Machine Learning and Information Processing
Prometheus instrumentation library for Python applications
Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filte…
Open source platform for the machine learning lifecycle