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FastAPI framework, high performance, easy to learn, fast to code, ready for production
Scalable machine 🤖 learning for time series forecasting.
Dataframes powered by a multithreaded, vectorized query engine, written in Rust
A unified framework for machine learning with time series
A unified framework for tabular probabilistic regression and probability distributions in python
A Python Library for interacting with the Power BI Rest API
MongoDB integrations for Apache Arrow. Export MongoDB documents to numpy array, parquet files, and pandas dataframes in one line of code.
PiML (Python Interpretable Machine Learning) toolbox for model development & diagnostics
Always know what to expect from your data.
A python library for user-friendly forecasting and anomaly detection on time series.
1 Line of code data quality profiling & exploratory data analysis for Pandas and Spark DataFrames.
PyGWalker: Turn your pandas dataframe into an interactive UI for visual analysis
Python Kalman filtering and optimal estimation library. Implements Kalman filter, particle filter, Extended Kalman filter, Unscented Kalman filter, g-h (alpha-beta), least squares, H Infinity, smoo…
Symbolic Aggregate approXimation, HOT-SAX, and SAX-VSM implementation in Python
Automatic extraction of relevant features from time series:
ruptures: change point detection in Python
A scikit-learn-compatible module to estimate prediction intervals and control risks based on conformal predictions.
FastAPI Best Practices and Conventions we used at our startup
A libre lightweight streaming front-end for Android.
This plugin extends Grafana Geomap panel with several functionalities: Support for GeoJSON shapes, Support for icons, Support for pop up visualizations of data from a specific point, Multiple layer…
OptaPy is an AI constraint solver for Python to optimize planning and scheduling problems.
Try PyScript: https://pyscript.com Examples: https://tinyurl.com/pyscript-examples Community: https://discord.gg/HxvBtukrg2
Online algorithms for solving large-scale dynamic vehicle routing problems with stochastic requests
Graph and network visualization using tabular data in R