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TimesFM (Time Series Foundation Model) is a pretrained time-series foundation model developed by Google Research for time-series forecasting.
High-Performance Symbolic Regression in Python and Julia
Tooling support for the Polylith Architecture in Python.
Plugin for Poetry to enable dynamic versioning based on VCS tags
A tiny scalar-valued autograd engine and a neural net library on top of it with PyTorch-like API
Create committing rules for projects 🚀 auto bump versions ⬆️ and auto changelog generation 📂
Repository containing notebooks of my posts on Medium
Azure MLOps (v2) solution accelerators. Enterprise ready templates to deploy your machine learning models on the Azure Platform.
aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)
Models and examples built with TensorFlow
[VLDB'22] Anomaly Detection using Transformers, self-conditioning and adversarial training.
PyNeuraLogic lets you use Python to create Differentiable Logic Programs
KDD 2019: Robust Anomaly Detection for Multivariate Time Series through Stochastic Recurrent Neural Network
PyTorch implementation of MTAD-GAT (Multivariate Time-Series Anomaly Detection via Graph Attention Networks) by Zhao et. al (2020, https://arxiv.org/abs/2009.02040).
A python library for user-friendly forecasting and anomaly detection on time series.
Kats, a kit to analyze time series data, a lightweight, easy-to-use, generalizable, and extendable framework to perform time series analysis, from understanding the key statistics and characteristi…
Probabilistic reasoning and statistical analysis in TensorFlow
PlaidML is a framework for making deep learning work everywhere.
ruptures: change point detection in Python
A JupyterLab plugin to facilitate invocation of code formatters.
Make drawing and labeling bounding boxes easy as cake