Microsoft connected vehicle sample code for the connected vehicle platform.
Обновлено 2022-11-02 01:13:28 +03:00
Documentation samples for ADX (Azure Data Explorer) service
Обновлено 2022-09-29 09:07:07 +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
Main purpose of this repo is to generate fake data to support demos, tests and sandboxes. This repo contains open source code in python, designed to work inside a Synapse workspace. It is built inside a Synapse notebook which fills all the tables of any industry database model.
Обновлено 2022-06-12 22:11:05 +03:00
Private Preview: Responsible AI Tooling in Azure Machine Learning
Обновлено 2022-03-28 19:01:33 +03:00
Обновлено 2021-12-22 12:57:50 +03:00
FTA AI Learning and Best Practices Resources
Обновлено 2021-11-30 02:56:47 +03:00
Preview: Test dataset support in Azure AutoML
Обновлено 2021-11-17 02:45:23 +03:00
AutoML code generation
Обновлено 2021-10-05 19:31:01 +03:00
Distributed training of Image segmentation on Azure Machine Learning
Обновлено 2021-02-17 22:47:57 +03:00
A tutorial demonstrating how to implement deep learning models for time series forecasting
Обновлено 2020-11-13 21:01:26 +03:00
Code for modelling estimated deaths and cases for COVID19.
Обновлено 2020-04-28 18:45:37 +03:00
Sample data for Microsoft Learn modules for Azure HDInsight
Обновлено 2020-02-21 01:12:12 +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
Batch scoring Spark models on Azure Databricks: A predictive maintenance use case
Обновлено 2019-05-24 16:44:02 +03:00
Active Learning Workshop Materials
Обновлено 2019-03-15 18:54:46 +03:00
Batch scoring deep learning models with kubernetes
Обновлено 2019-02-07 16:46:58 +03:00
How to deploy Python models on a Kubernetes cluster
Обновлено 2019-02-01 22:07:32 +03:00
Batch AI for anomaly detection
Обновлено 2019-01-29 00:27:59 +03:00
Getting Started with ADLA with R
Обновлено 2018-11-20 18:21:14 +03:00
Population Health Management
Обновлено 2018-10-01 15:06:28 +03:00
Notebooks for the Azure ML Text Analytics Package
Обновлено 2018-07-19 20:11:43 +03:00
This repo aims to showcase how to deploy deep learning models.
Обновлено 2018-06-26 21:46:23 +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
A tutorial demonstrating how to train a neural network to play hangman using CNTK
Обновлено 2017-11-02 21:07:18 +03:00
Predictive Maintenance using Pyspark
Обновлено 2017-09-12 00:08:06 +03:00
This repository stores several Notebooks that implements multiple Document Matching data science approaches and evaluation metrics.
Обновлено 2017-08-30 23:27:07 +03:00
LSTMS for Predictive Maintenance
Обновлено 2017-07-31 23:19:07 +03:00