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
An example of using OpenCV dnn module with YOLOv5. (ObjectDetection, Segmentation, Classification)
Обновлено 2024-03-09 22:49:38 +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
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
Text classification solution with Microsoft Machine Learning Server
Обновлено 2023-06-12 22:32:06 +03:00
Deep Metric Transfer for Label Propagation with Limited Annotated Data
Обновлено 2023-06-03 07:09:23 +03:00
To gain access, please finish setting up this repository now at: https://repos.opensource.microsoft.com/microsoft/wizard?existingreponame=SpeciesClassification&existingrepoid=169153301
Обновлено 2023-05-01 23:51:33 +03:00
Ramp up your custom natural language processing (NLP) task, allowing you to bring your own data, use your preferred frameworks and bring models into production.
nlp
ner
classification
question-answering
dstoolkit
machine-reading-comprehension
summarization
transformer
Обновлено 2022-01-10 02:07:54 +03:00
Provably defending pretrained classifiers including the Azure, Google, AWS, and Clarifai APIs
machine-learning
deep-learning
computer-vision
neural-networks
image-classification
azure-computer-vision
clarifai
google-cloud-vision
provable-defense
adversarial-defense
adversarial-examples
adversarial-robustness
aws-rekognition
Обновлено 2021-04-03 00:37:13 +03:00
Quantum Classification tutorial using Microsoft Quantum Development Kit
Обновлено 2020-12-03 10:04:00 +03:00
Tutorial demonstrating how to create a semantic segmentation (pixel-level classification) model to predict land cover from aerial imagery. This model can be used to identify newly developed or flooded land. Uses ground-truth labels and processed NAIP imagery provided by the Chesapeake Conservancy.
microsoft
azure-storage
image-classification
neural-networks
cntk
microsoft-azure
land-cover
land-use
geospatial-data
image-segmentation
microsoft-machine-learning
azure-batchai
cntk-model
geospatial-analysis
Обновлено 2019-07-25 06:53:28 +03:00
Sample of how to develop & deploy text classification models using Azure ML package for Text Analytics and Team Data Science Process (TDSP
Обновлено 2018-06-20 18:43:02 +03:00