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 2024-09-14 09:32:19 +03:00
Official community-driven Azure Machine Learning examples, tested with GitHub Actions.
Обновлено 2024-09-12 20:11:30 +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 2024-09-09 22:56:21 +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 2024-09-09 20:11:25 +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
12 Weeks, 24 Lessons, AI for All!
Обновлено 2024-08-31 02:58:02 +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
Knowledge Extraction For Forms Accelerators & Examples
Обновлено 2024-07-09 20:31:09 +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
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
FastTrack for Azure AzureML Live event
Обновлено 2023-07-28 08:06:17 +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
Interactive Neural Machine Translation tool
Обновлено 2023-07-15 01:45:30 +03:00
Running the most popular deep learning frameworks on Azure Batch AI
Обновлено 2023-06-12 22:32:13 +03:00
End-to-End recipes for pre-training and fine-tuning BERT using Azure Machine Learning Service
nlp
pytorch
azure-machine-learning
language-model
bert
tuning
finetuning
pretraining
azureml-bert
bert-model
pretrained-models
Обновлено 2023-06-12 21:59:00 +03:00
Обновлено 2023-03-29 18:17:50 +03:00
Synthetic Dataset Insights
Обновлено 2022-09-23 22:35:49 +03:00
Tools and Docs on the Azure Data Science Virtual Machine (http://aka.ms/dsvm)
azure
python
machine-learning
deep-learning
data-science
r
ai
ml
big-data
sqlserver
data-analysis
dsvm
Обновлено 2022-09-18 21:35:33 +03:00
Solution accelerator to help build Machine Learning Lineage
Обновлено 2022-09-17 00:05:08 +03:00
MCW Analyzing text with Azure Machine Learning and Cognitive Services
Обновлено 2022-07-01 19:44:55 +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
Deploying a Batch Scoring Pipeline for Python Models
Обновлено 2020-01-28 22:21:04 +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
Show how to perform fast retraining with LightGBM in different business cases
azure
machine-learning
benchmark
gpu
lightgbm
distributed-systems
gbdt
xgboost
gbm
gbrt
kaggle
boosted-trees
Обновлено 2019-07-18 11:16:44 +03:00