Metric Libraries

44 Components & Libraries

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Metric Libraries

A highly scalable real-time graphing system

Graphite consists of three major components:

An open-source, cloud-native, distributed time-series database with PromQL/SQL/Python supported. Available on GreptimeCloud.

Our core developers have been building time-series data platforms for years. Based on our best-practices, GreptimeDB is born to give you: Seamless scalability from a standalone binary at edge to a ro…

ALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Intelligence concepts to economic decision making. One of its goals is to build a toolkit that combines state-of-the-art machine learning techniques with econometrics in order to bring automation to complex causal inference problems. To date, the ALICE Python SDK (econml) implements orthogonal machine learning algorithms such as the double machine learning work of Chernozhukov et al. This toolkit is designed to measure the causal effect of some treatment variable(s) t on an outcome variable y, controlling for a set of features x.

You can also perform direct policy learning from observational data, using the doubly robust method for offline policy learning. These methods directly predict a recommended treatment, without intern…

StellarGraph - Machine Learning on Graphs

Graph-structured data represent entities as nodes (or vertices) and relationships between them as edges (or links), and can include data associated with either as attributes. For example, a graph can…

ALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Intelligence concepts to economic decision making. One of its goals is to build a toolkit that combines state-of-the-art machine learning techniques with econometrics in order to bring automation to complex causal inference problems. To date, the ALICE Python SDK (econml) implements orthogonal machine learning algorithms such as the double machine learning work of Chernozhukov et al. This toolkit is designed to measure the causal effect of some treatment variable(s) t on an outcome variable y, controlling for a set of features x.

A python parametric CAD scripting framework based on OCCT

CadQuery is an intuitive, easy-to-use Python module for building parametric 3D CAD models. Using CadQuery, you can write short, simple scripts that produce high quality CAD models. It is easy to make…

Lecture Notes for Linear Algebra Featuring Python. This series of lecture notes will walk you through all the must-know concepts that set the foundation of data science or advanced quantitative skillsets. Suitable for statistician/econometrician, quantitative analysts, data scientists and etc. to quickly refresh the linear algebra with the assistance of Python computation and visualization.

These lecture notes are intended for introductory linear algebra courses, suitable for university students, programmers, data analysts, algorithmic traders and etc. The lectures notes are loosely bas…

Easy to use cryptographic framework for data protection: secure messaging with forward secrecy and secure data storage. Has unified APIs across 14 platforms.

Themis is an open-source high-level cryptographic services library for securing data during authentication, storage, messaging, network exchange, etc. Themis solves 90% of typical data protection use…

Lecture Notes for Linear Algebra Featuring Python. This series of lecture notes will walk you through all the most must-know concepts that set the foundation of data science or advanced quantitative skillsets. Suitable for statistician/econometrician, quantitative analysts, data scientists and etc. to quickly refresh the linear algebra with the assistance of Python computation and visualization.

Torchmetrics - Machine learning metrics for distributed, scalable PyTorch applications.

Simple installation from PyPI Install using conda Pip from source Pip from archive Extra dependencies for specialized metrics: Install latest developer version TorchMetrics is a collection of 100+ Py…

Metric learning algorithms in Python

If you use metric-learn in a scientific publication, we would appreciate citations to the following paper: Bibtex entry:

Machine learning metrics for distributed, scalable PyTorch applications.

Open source person re-identification library in python

Open-ReID is a lightweight library of person re-identification for research purpose. It aims to provide a uniform interface for different datasets, a full set of models and evaluation metrics, as wel…

:zap: Data quality management for SQL, Spark, and Pandas-accessible data

Soda Core is a free, open-source, command-line tool that enables you to use the Soda Checks Language to turn user-defined input into aggregated SQL queries. When it runs a scan on a dataset, Soda Cor…

Python code to fuse multiple RGB-D images into a TSDF voxel volume.

This is a lightweight python script that fuses multiple registered color and depth images into a projective truncated signed distance function (TSDF) volume, which can then be used to create high qua…

Command line interface used by all WakaTime text editor plugins.

Install the plugin for your IDE/editor: Each plugin either comes pre-bundled with WakaTime CLI, or downloads the latest version from GitHub for you. Each plugin also has its own log file: Useful API …

Machine learning metrics for distributed, scalable PyTorch applications.

Instrument your FastAPI with Prometheus metrics.

Instrument your app with default metrics and expose the metrics: Depending on your code you might have to use the following instead: With this, your FastAPI is instrumented and metrics are ready to b…

Python library and web service for Open Source Software Health and Sustainability metrics & data collection. You can find our documentation and new contributor information easily here: https://oss-augur.readthedocs.io/en/main/ and learn more about Augur at our website https://augurlabs.io

We gather trace data for a group of repositories, normalize it into our data model, and provide a variety of metrics about said data. The structure of our data model enables us to synthesize data acr…

Machine learning for multivariate data through the Riemannian geometry of positive definite matrices in Python

This code is BSD-licensed (3 clause). or using pip+git for the latest version of the code: or in editable mode to be able to modify the sources: If you make a modification, run the test suite before …

TypeDB-ML is the Machine Learning integrations library for TypeDB

You may find the following resources useful, particularly to understand why TypeDB-ML started: Python >= 3.7.x It's expected that you will use Pip to install, but should you need to make your own …

Fast EMD for Python: a wrapper for Pele and Werman's C++ implementation of the Earth Mover's Distance metric

You can also get the associated minimum-cost flow: You can also calculate the EMD directly from two arrays of observations:

PyNLPl, pronounced as 'pineapple', is a Python library for Natural Language Processing. It contains various modules useful for common, and less common, NLP tasks. PyNLPl can be used for basic tasks such as the extraction of n-grams and frequency lists, and to build simple language model. There are also more complex data types and algorithms. Moreover, there are parsers for file formats common in NLP (e.g. FoLiA/Giza/Moses/ARPA/Timbl/CQL). There are also clients to interface with various NLP specific servers. PyNLPl most notably features a very extensive library for working with FoLiA XML (Format for Linguistic Annotation).

PyNLPl, pronounced as 'pineapple', is a Python library for Natural Language Processing. It contains various modules useful for common, and less common, NLP tasks. PyNLPl can be used for basic tasks s…

Observe FastAPI app with three pillars of observability: Traces (Tempo), Metrics (Prometheus), Logs (Loki) on Grafana through OpenTelemetry and OpenMetrics.

Start all services with docker-compose Dashboard screenshot: Grafana provides a great solution, which could observe specific actions in service between traces, metrics, and logs through trace ID and …

DoubleML - Double Machine Learning in Python

It further can be readily extended with regards to To install DoubleML with pip use DoubleML can be installed from source via If you use the DoubleML package a citation is highly appreciated: Bibtex-…

🗣️ Tool to generate adversarial text examples and test machine learning models against them

This library allows you to generate texts using these methods, and simulate these kind of attacks on your machine learning models. By exposing your model to these texts offline, you will be able to b…

Using oriented gabor filters to enhance fingerprint images

Uses oriented gabor filter bank to enhance the fingerprint image. The orientation of the gabor filters is decided by the orientation of ridges in the input image. The sample images are stored in the …

A metric for Perceptual Image-Error Assessment through Pairwise Preference (PieAPP at CVPR 2018).

In this repo, we provide the Tensorflow and PyTorch implementations of our evaluation code for PieAPP v0.1 along with the trained models. We also provide a Win64 command-line executable. The input to…

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