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
Running the most popular deep learning frameworks on Azure Batch AI
Обновлено 2023-06-12 22:32:13 +03:00
Datasets, tools, and benchmarks for representation learning of code.
machine-learning
deep-learning
data-science
ml
python
tensorflow
neural-networks
open-data
datasets
cnn
machine-learning-on-source-code
natural-language-processing
nlp
nlp-machine-learning
bert
programming-language-theory
representation-learning
rnn
self-attention
data
Обновлено 2022-01-31 12:25:07 +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
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