| page_type | languages | products | description | ||
|---|---|---|---|---|---|
sample |
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Top-level directory for official Azure Machine Learning CLI sample code. |
Welcome to the Azure Machine Learning examples repository!
-
An Azure subscription. If you don't have an Azure subscription, create a free account before you begin.
-
A terminal. Install and set up the CLI (v2) before you begin.
-
Clone this repository:
git clone https://github.com/Azure/azureml-examples --depth 1 cd azureml-examples/cli -
Run the setup script and create compute:
bash setup.sh bash create-compute.sh
- Train models (create jobs) with the CLI (v2)
- Deploy and score a model using a managed online endpoint
Scripts
Jobs (jobs)
| path | status | description |
|---|---|---|
| jobs/dataprep/dask/nyctaxi/job.yml |  |
This sample shows how to run a distributed DASK job on AzureML. |
| jobs/dataprep/spark/nyctaxi/job.yml |  |
This sample shows how to run a single node Spark job on AzureML. |
| jobs/logging/julia/iris/job.yml |  |
Train a Flux model on the Iris dataset. Showcases examples of mlflow logging API used in training |
| jobs/logging/sklearn/iris/job.yml |  |
Train a scikit-learn knn model on the iris dataset. Showcases examples of mlflow logging API's used in training. |
| jobs/train/fastai/mnist/job.yml |  |
Train a RESNET-18 convolutional neural network (CNN) with fast.ai on the MNIST dataset. |
| jobs/train/fastai/pets/job.yml |  |
Fine tune a convolutional neural network (CNN) with fast.ai on a pets dataset. |
| jobs/train/julia/iris/job.yml |  |
Train a Flux model on the Iris dataset. |
| jobs/train/lightgbm/iris-bash/job.yml |  |
Train a LightGBM model on the Iris dataset via Python via Bash script. |
| jobs/train/lightgbm/iris/job-sweep.yml |  |
Run a hyperparameter sweep job for LightGBM on Iris dataset. |
| jobs/train/lightgbm/iris/job.yml |  |
Train a LightGBM model on the Iris dataset. |
| jobs/train/pytorch/iris/job.yml |  |
Train a neural network with PyTorch on the Iris dataset. |
| jobs/train/pytorch/word-language-model/job.yml |  |
Train a multi-layer RNN (Elman, GRU, or LSTM) on a language modeling task with PyTorch. |
| jobs/train/r/accidents/job.yml |  |
Train a GLM using R on the accidents dataset. |
| jobs/train/r/iris/job.yml |  |
Train an R model on the Iris dataset. |
| jobs/train/scikit-learn/diabetes/job.yml |  |
Train a scikit-learn LinearRegression model on the Diabetes dataset. |
| jobs/train/scikit-learn/iris/job.yml |  |
Train a scikit-learn SVM on the Iris dataset. |
| jobs/train/scikit-learn/mnist/job.yml |  |
Train a scikit-learn LogisticRegression model on the MNSIT dataset. |
| jobs/train/tensorflow/iris/job.yml |  |
Train a Tensorflow Decision Forest on the Iris dataset. |
| jobs/train/tensorflow/mnist-distributed-horovod/job.yml |  |
Train a basic neural network with TensorFlow on the MNIST dataset, distributed via Horovod. |
| jobs/train/tensorflow/mnist-distributed/job.yml |  |
Train a basic neural network with TensorFlow on the MNIST dataset, distributed via TensorFlow. |
| jobs/train/tensorflow/mnist/job.yml |  |
Train a basic neural network with TensorFlow on the MNIST dataset. |
| jobs/misc/hello-world-env-var.yml |  |
no description |
| jobs/misc/hello-world.yml |  |
no description |
Endpoints (endpoints)
| path | status | description |
|---|
Assets (assets)
| path | status | description |
|---|---|---|
| assets/data/iris-datastore.yml |  |
Data asset from datastore blob storage. |
| assets/data/iris-url.yml |  |
Data asset pointing to Iris CSV on public blob storage. |
| assets/environment/python-ml-basic-cpu.yml |  |
Environment asset created from a base Docker image plus a Conda environment file. |
| assets/model/lightgbm-iris.yml |  |
Model asset from local directory. |
| directory | description |
|---|---|
assets |
assets |
endpoints |
endpoints |
jobs |
jobs |
We welcome contributions and suggestions! Please see the contributing guidelines for details.
This project has adopted the Microsoft Open Source Code of Conduct. Please see the code of conduct for details.