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.
Обновлено 2024-11-08 19:55:46 +03:00
A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.
Обновлено 2024-11-08 09:19:21 +03:00
ML.NET is an open source and cross-platform machine learning framework for .NET.
Обновлено 2024-11-05 20:27:05 +03:00
Qlib is an AI-oriented quantitative investment platform that aims to realize the potential, empower research, and create value using AI technologies in quantitative investment, from exploring ideas to implementing productions. Qlib supports diverse machine learning modeling paradigms. including supervised learning, market dynamics modeling, and RL.
Обновлено 2024-09-12 18:44:27 +03:00
A set of tools to use in Microsoft Azure Form Recognizer and OCR services.
Обновлено 2024-09-04 06:49:14 +03:00
Cyclic Boosting Machines - an explainable supervised machine learning algorithm
Обновлено 2024-09-04 00:22:24 +03:00
A dataset of real DNA traces for benchmarking trace reconstruction algorithms
Обновлено 2024-08-13 21:17:32 +03:00
An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.
Обновлено 2024-07-03 13:54:08 +03:00
Experience, Learn and Code the latest breakthrough innovations with Microsoft AI
Обновлено 2024-06-26 22:42:37 +03:00
Multi-species bioacoustic classification using deep learning algorithms
Обновлено 2024-06-18 01:58:08 +03:00
Samples for ML.NET, an open source and cross-platform machine learning framework for .NET.
Обновлено 2024-04-29 23:02:02 +03:00
JsonToJsonMapper works on JSON format to exchange information between systems. It enables transformation of JSON data from one schema to another.
Обновлено 2024-02-25 20:50:47 +03:00
Multi-Agent Resource Optimization (MARO) platform is an instance of Reinforcement Learning as a Service (RaaS) for real-world resource optimization problems.
Обновлено 2024-02-23 11:45:58 +03:00
A fast algorithm to optimally compose privacy guarantees of differentially private (DP) mechanisms to arbitrary accuracy.
Обновлено 2024-02-15 16:24:04 +03:00
Algorithms for doing leader election and name resolving with the help of another HA system, serve as anticorruption layers.
Обновлено 2024-01-16 22:51:13 +03:00
quantum-viz.js is a configurable tool for rendering quantum circuits using pure HTML.
Обновлено 2023-08-15 02:14:12 +03:00
An algorithm for cross-domain NL2SQL
Обновлено 2023-07-22 23:20:17 +03:00
Synthesizer for optimal collective communication algorithms
Обновлено 2023-07-21 21:16:40 +03:00
Various algorithm to control things
Обновлено 2023-07-18 21:18:48 +03:00
This repository provides code for machine learning algorithms for edge devices developed at Microsoft Research India.
Обновлено 2023-07-07 00:42:22 +03:00
A novel embedding training algorithm leveraging ANN search and achieved SOTA retrieval on Trec DL 2019 and OpenQA benchmarks
Обновлено 2023-06-13 00:27:31 +03:00
R-powered custom visual implementing the “Seasonal and Trend decomposition using Loess” algorithm, offering several types of plots. Time series decomposition is an essential analytics tool to understand the time series components and to improve forecasting.
Обновлено 2023-06-12 23:28:34 +03:00
TestApi is a library of test and utility APIs that enables developers and testers to create testing tools and automated tests for .NET and Win32 applications. TestApi provides a set of common test building blocks -- types, data-structures and algorithms -- in a simple, layered, componentized and documented stack.
Обновлено 2023-06-12 23:27:26 +03:00
Code for the neural architecture search methods contained in the paper Efficient Forward Neural Architecture Search
Обновлено 2023-06-12 21:22:32 +03:00
Logarithmic Reinforcement Learning
Обновлено 2023-03-25 04:36:23 +03:00
SIDH Library is a fast and portable software library that implements state-of-the-art supersingular isogeny cryptographic schemes. The chosen parameters aim to provide security against attackers running a large-scale quantum computer, and security against classical algorithms.
Обновлено 2022-12-12 04:16:18 +03:00