TorchGeo: datasets, samplers, transforms, and pre-trained models for geospatial data
Обновлено 2024-09-16 02:39:57 +03:00
Training pipelines for Firefox Translations neural machine translation models
Обновлено 2024-09-13 23:44:39 +03:00
Verify is a snapshot tool that simplifies the assertion of complex data models and documents.
Обновлено 2024-09-13 14:51:14 +03:00
Example models using DeepSpeed
Обновлено 2024-09-13 00:22:30 +03:00
CPU-optimized Neural Machine Translation models for Firefox Translations
Обновлено 2024-09-12 22:24:21 +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.
machine-learning
deep-learning
python
platform
research
finance
algorithmic-trading
auto-quant
fintech
investment
paper
quant
quant-dataset
quant-models
quantitative-finance
quantitative-trading
research-paper
stock-data
Обновлено 2024-09-12 18:44:27 +03:00
Sharing Updatable Models (SUM) on Blockchain
machine-learning
python
react
ai
ml
artificial-intelligence
node
economics
blockchain
ethereum
prediction-mar
prediction-market
smart-contracts
truffle
Обновлено 2024-09-11 00:34:15 +03:00
Infer.NET is a framework for running Bayesian inference in graphical models
Обновлено 2024-09-05 02:51:09 +03:00
SkiaSharp is a cross-platform 2D graphics API for .NET platforms based on Google's Skia Graphics Library. It provides a comprehensive 2D API that can be used across mobile, server and desktop models to render images.
hacktoberfest
dotnet
macos
xamarin
windows
android
ios
graphics
cross-platform
skiasharp
dot-net
skia
Обновлено 2024-09-04 17:22:13 +03:00
Ongoing research training transformer language models at scale, including: BERT & GPT-2
Обновлено 2024-09-04 08:42:52 +03:00
DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphical models and potential outcomes frameworks.
machine-learning
data-science
causal-inference
causality
treatment-effects
bayesian-networks
causal-machine-learning
causal-models
do-calculus
graphical-models
python3
Обновлено 2024-08-29 21:13:51 +03:00
Large-scale Self-supervised Pre-training Across Tasks, Languages, and Modalities
nlp
multimodal
beit
beit-3
deepnet
document-ai
foundation-models
kosmos
kosmos-1
layoutlm
layoutxlm
llm
minilm
mllm
pre-trained-model
textdiffuser
trocr
unilm
xlm-e
Обновлено 2024-08-28 08:15:16 +03:00
Hummingbird compiles trained ML models into tensor computation for faster inference.
Обновлено 2024-08-23 12:06:25 +03:00
This package features data-science related tasks for developing new recognizers for Presidio. It is used for the evaluation of the entire system, as well as for evaluating specific PII recognizers or PII detection models.
machine-learning
deep-learning
nlp
natural-language-processing
privacy
ner
transformers
pii
named-entity-recognition
spacy
flair
Обновлено 2024-08-07 19:17:23 +03:00
Обновлено 2024-07-31 17:58:35 +03:00
A DNN inference latency prediction toolkit for accurately modeling and predicting the latency on diverse edge devices.
machine-learning
python
deep-learning
pytorch
neural-architecture-search
deep-neural-networks
edge-computing
latency
inference
edge-ai
efficient-model
onnx-models
tensorflow-models
Обновлено 2024-07-31 00:16:53 +03:00
This repo contains the scripts, models, and required files for the Deep Noise Suppression (DNS) Challenge.
Обновлено 2024-07-25 13:19:02 +03:00
Contains JavaScript & TypeScript object models for Microsoft Power BI JavaScript SDK
Обновлено 2024-07-23 17:59:26 +03:00
Cross-platform UI for interacting with devices attached to Azure IoT Hub
Обновлено 2024-06-18 10:01:06 +03:00
NPM package for TensorFlow.js models exported from Custom Vision Service
Обновлено 2024-06-17 18:54:50 +03:00
Subseasonal forecasting models
Обновлено 2024-06-03 17:10:34 +03:00
VideoX: a collection of video cross-modal models
Обновлено 2024-06-03 05:11:25 +03:00
Code to reproduce experiments in the paper "Constrained Language Models Yield Few-Shot Semantic Parsers" (EMNLP 2021).
Обновлено 2024-05-31 20:48:22 +03:00
Azure MLOps (v2) solution accelerators. Enterprise ready templates to deploy your machine learning models on the Azure Platform.
azure
microsoft
machine-learning
deep-learning
devops
azureml
mlops
azuremachinelearning
mlops-environment
mlops-template
mlops-workflow
mlops-project
Обновлено 2024-04-19 06:43:42 +03:00
Azure Remote Rendering Toolkit (ARRT) assists with uploading, converting, and rendering 3D models using the Azure Remote Rendering service.
Обновлено 2024-04-03 12:38:24 +03:00
Fit Sparse Synthetic Control Models in Python
Обновлено 2024-03-26 21:53:01 +03:00
InnerEye dataset creation tool for InnerEye-DeepLearning library. Transforms DICOM data into mask for training Deep Learning models.
Обновлено 2024-03-21 12:52:00 +03:00
The InnerEye-Gateway is a Windows service that acts as a DICOM end point to run inference on https://github.com/microsoft/InnerEye-DeepLearning models.
Обновлено 2024-03-21 12:50:43 +03:00
Enables inference and deployment of InnerEye-DeepLearning (https://github.com/microsoft/InnerEye-deeplearning) models as an async REST API on Azure
Обновлено 2024-03-21 12:48:29 +03:00