Tutorials and programming exercises for learning Q# and quantum computing
Обновлено 2024-01-12 21:40:42 +03:00
maximal update parametrization (µP)
Обновлено 2023-10-21 06:45:36 +03:00
Best Practices, code samples, and documentation for Computer Vision.
microsoft
azure
machine-learning
python
deep-learning
data-science
computer-vision
kubernetes
artificial-intelligence
object-detection
tutorial
jupyter-notebook
convolutional-neural-networks
image-classification
image-processing
operationalization
similarity
Обновлено 2023-10-18 19:13:00 +03:00
Jupyter Notebooks on Azure for Genomics Data Analysis
Обновлено 2023-10-09 23:25:33 +03:00
Spit shine for Jupyter notebooks 🧽✨
Обновлено 2023-10-04 02:29:31 +03:00
Style Normalization and Restitution for Domain Generalization and Adaptation
Обновлено 2023-10-04 00:19:13 +03:00
Build sim from data for use in reinforcement learning and bonsai platform for machine teaching.
Обновлено 2023-09-07 19:12:44 +03:00
🌱 Join a community of developers at Microsoft Reactor and connect with people, skills, and technology to build your career or personal learning. We offer free livestreams, on-demand content, and hybrid/in-person events daily around the world. Access our projects and code here.
dotnet
azure
python
data-science
nodejs
ai
ml
mixed-reality
devops
iot
web
data
cloud
events
low-code
live-streaming
meetup
no-code
personal-de
Обновлено 2023-09-01 14:55:23 +03:00
Debugging, monitoring and visualization for Python Machine Learning and Data Science
machine-learning
python
deep-learning
data-science
ai
monitoring
reinforcement-learning
jupyter
jupyter-notebook
debugging
deeplearning
debug
machinelearning
explainable-ai
explainable-ml
saliency
debugging-tool
model-visualization
Обновлено 2023-08-30 10:47:36 +03:00
With AutoBrewML Framework the time it takes to get production-ready ML models with great ease and efficiency highly accelerates.
microsoft
machine-learning
data-science
anomaly-detection
nlp-machine-learning
sampling-strategies
text-analysis
text-classification
text-summarization
azure-automl
cleansing-data
datavisualization
responsible-ml
Обновлено 2023-08-03 09:43:02 +03:00
Genalog is an open source, cross-platform python package allowing generation of synthetic document images with custom degradations and text alignment capabilities.
machine-learning
python
data-science
ner
synthetic-data
synthetic-data-generation
data-generation
ocr-recognition
synthetic-images
text-alignment
Обновлено 2023-07-20 18:03:32 +03:00
Install and Use .Net Interactive Kernels in ADS
Обновлено 2023-07-19 05:33:46 +03:00
A collection of libraries for interfacing simulators with the Bonsai platform.
Обновлено 2023-07-19 01:59:47 +03:00
Repo for accelerated Spark demo at //build 20.
Обновлено 2023-07-19 01:15:06 +03:00
Interactive Neural Machine Translation tool
Обновлено 2023-07-15 01:45:30 +03:00
Normalized Trend Filtering for Biomedical Datasets
Обновлено 2023-07-07 01:07:14 +03:00
workspace to share scripts and utilities used by mssql support team
Обновлено 2023-06-30 23:43:49 +03:00
Jupyter Notebook with Python samples for the Cognitive Services Computer Vision API
Обновлено 2023-06-27 16:07:21 +03:00
Python SDK for the Microsoft Emotion API, part of Cognitive Services
Обновлено 2023-06-27 16:07:21 +03:00
SQL Server 2019 Workshop
Обновлено 2023-06-27 15:57:02 +03:00
Advanced analytics samples and templates with Python for ML Server
Обновлено 2023-06-12 23:27:15 +03:00
End-to-end guide design for CRISPR/Cas9 with machine learning
Обновлено 2023-06-12 23:26:53 +03:00
Campaign optimization solution with SQL Server ML Services
Обновлено 2023-06-12 23:01:40 +03:00
Running the most popular deep learning frameworks on Azure Batch AI
Обновлено 2023-06-12 22:32:13 +03:00
Scenarios, tutorials and demos for Autonomous Driving
microsoft
deep-learning
simulation
tensorflow
robotics
tutorial
autonomous-vehicles
airsim
self-driving-car
autonomous-driving
autonomous-driving-cookbook
car
cntk
keras
microsoft-garage
Обновлено 2023-06-12 22:32:09 +03:00
Text classification solution with Microsoft Machine Learning Server
Обновлено 2023-06-12 22:32:06 +03:00
This project created to analyze, compare and identify whale tails from the Kaggle competition dataset, "Humpback Whale Identification Challenge". It is written in Python, and uses the Keras API with Tensorflow backend. The project implemented both a Siamese Network and a SoftMax classifier with center loss.
Обновлено 2023-06-12 22:29:42 +03:00
Quick useful examples of data science & ML & big data
Обновлено 2023-06-12 22:28:36 +03:00