Detect and warn about suspicious IPs logging into Nextcloud
Обновлено 2024-09-07 16:25:35 +03:00
Simple and Distributed Machine Learning
azure
microsoft
machine-learning
deep-learning
ai
data-science
opencv
ml
cognitive-services
spark
http
big-data
lightgbm
databricks
onnx
apache-spark
pyspark
scala
model-deployment
synapse
Обновлено 2024-09-07 07:25:44 +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.
machine-learning
microsoft
python
distributed
data-mining
decision-trees
gbdt
gbm
gbrt
gradient-boosting
kaggle
lightgbm
parallel
r
Обновлено 2024-09-07 02:24:59 +03:00
DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.
machine-learning
deep-learning
pytorch
gpu
compression
billion-parameters
data-parallelism
inference
mixture-of-experts
model-parallelism
pipeline-parallelism
trillion-parameters
zero
Обновлено 2024-09-07 00:48:18 +03:00
Platform for Machine Learning projects on Software Engineering
Обновлено 2024-09-07 00:21:14 +03:00
ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator
machine-learning
deep-learning
pytorch
tensorflow
neural-networks
scikit-learn
ai-framework
hardware-acceleration
onnx
Обновлено 2024-09-06 21:52:20 +03:00
Best Practices on Recommendation Systems
azure
microsoft
machine-learning
python
deep-learning
kubernetes
data-science
artificial-intelligence
jupyter-notebook
tutorial
operationalization
ranking
rating
recommendation
recommendation-algorithm
recommendation-engine
recommendation-system
recommender
Обновлено 2024-09-06 10:53:41 +03:00
A fast library for AutoML and tuning. Join our Discord: https://discord.gg/Cppx2vSPVP.
machine-learning
deep-learning
data-science
python
automated-machine-learning
natural-language-processing
hyperparameter-optimization
automl
jupyter-notebook
timeseries-forecasting
tuning
classification
finetuning
hyperparam
natural-language-generation
random-forest
regression
scikit-learn
tabular-data
Обновлено 2024-09-06 07:00:13 +03:00
VS Code Jupyter extension
Обновлено 2024-09-05 19:57:16 +03:00
Infer.NET is a framework for running Bayesian inference in graphical models
Обновлено 2024-09-05 02:51:09 +03:00
The Unity Machine Learning Agents Toolkit (ML-Agents) is an open-source project that enables games and simulations to serve as environments for training intelligent agents using deep reinforcement learning and imitation learning.
unity
machine-learning
unity3d
deep-learning
reinforcement-learning
neural-networks
deep-reinforcement-learning
Обновлено 2024-09-04 16:23:04 +03:00
A set of tools to use in Microsoft Azure Form Recognizer and OCR services.
machine-learning
typescript
machine-learning-algorithms
rpa
form-recognizer
labeling-tool
ocr-form-labeling
Обновлено 2024-09-04 06:49:14 +03:00
DeepSpeech is an open source embedded (offline, on-device) speech-to-text engine which can run in real time on devices ranging from a Raspberry Pi 4 to high power GPU servers.
machine-learning
deep-learning
tensorflow
neural-networks
embedded
speech-recognition
deepspeech
offline
on-device
speech-to-text
Обновлено 2024-09-04 00:17:43 +03:00
To gain access, please finish setting up this repository now at: https://repos.opensource.microsoft.com/microsoft/wizard?existingreponame=CameraTraps&existingrepoid=152634113
Обновлено 2024-09-03 21:25:01 +03:00
HI-ML toolbox for deep learning for medical imaging and Azure integration
Обновлено 2024-09-03 14:16:21 +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 2024-09-03 13:09:15 +03:00
ML.NET is an open source and cross-platform machine learning framework for .NET.
Обновлено 2024-09-03 00:03:10 +03:00
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 2024-09-02 22:50:34 +03:00
12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all
machine-learning
python
data-science
ml
scikit-learn
r
machine-learning-algorithms
machinelearning
education
scikit-learn-python
machinelearning-python
Обновлено 2024-08-31 08:16:34 +03:00
12 Weeks, 24 Lessons, AI for All!
Обновлено 2024-08-31 02:58:02 +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
Hummingbird compiles trained ML models into tensor computation for faster inference.
Обновлено 2024-08-23 12:06:25 +03:00
The ORBIT dataset is a collection of videos of objects in clean and cluttered scenes recorded by people who are blind/low-vision on a mobile phone. The dataset is presented with a teachable object recognition benchmark task which aims to drive few-shot learning on challenging real-world data.
microsoft
machine-learning
computer-vision
video
benchmark
dataset
classification
few-shot-learning
meta-learning
object-recognition
Обновлено 2024-08-13 03:27:45 +03:00
Explore machine learning and data science with Codespaces
Обновлено 2024-08-12 16:11:43 +03:00
Python notebooks with ML and deep learning examples with Azure Machine Learning Python SDK | Microsoft
Обновлено 2024-08-08 18:36:05 +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
Responsible AI Toolbox is a suite of tools providing model and data exploration and assessment user interfaces and libraries that enable a better understanding of AI systems. These interfaces and libraries empower developers and stakeholders of AI systems to develop and monitor AI more responsibly, and take better data-driven actions.
machine-learning
data-science
ml
visualization
jupyter
data-visualization
ui
machinelearning
widgets
data-analysis
explainable-ai
explainable-ml
fairness-ai
fairness-ml
interpretability
fairness
responsible-ai
explainability
widget
error-analysis
Обновлено 2024-08-07 04:34:48 +03:00
Responsible AI Toolbox is a suite of tools providing model and data exploration and assessment user interfaces and libraries that enable a better understanding of AI systems. These interfaces and libraries empower developers and stakeholders of AI systems to develop and monitor AI more responsibly, and take better data-driven actions.
machine-learning
data-science
jupyter
ml
ui
explainable-ai
explainable-ml
fairness
fairness-ai
fairness-ml
interpretability
machinelearning
responsible-ai
visualization
widget
widgets
data-analysis
data-visualization
error-analysis
explainability
Обновлено 2024-08-07 04:34:48 +03:00
Microsoft Finance Time Series Forecasting Framework (FinnTS) is a forecasting package that utilizes cutting-edge time series forecasting and parallelization on the cloud to produce accurate forecasts for financial data.
microsoft
machine-learning
deep-learning
data-science
r
finance
time-series
forecasting
business
finnts
r-package
rstats
Обновлено 2024-08-05 18:19:32 +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