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Tutorials

Welcome to the UbiOps tutorials page!

The UbiOps tutorials page is here to provide (new) users with inspiration on how to work with UbiOps. Use it to find inspiration or to discover new ways of working with the UbiOps platform.

With a (free) UbiOps account you can use the tutorials to have example applications running in your own environment in minutes.*

How does it work?

We have three tutorial categories: All of our tutorials contain full walkthroughs that can be run in Jupyter notebook or Rstudio. Except for the UI tutorials, they contain ready-to-go deployment packages which illustrate how to use the deployment package for typical cases, using the WebApp.

Requirements

To be able to use the UbiOps tutorials you need three things:

  • You need to have the UbiOps client library installed. For Python this can be done via pip install or via Setuptools. For more information see our GitHub Python page. For R this can be done by installing the devtools package and then using the install_github function. For more information see our GitHub R page

  • If you want to run Python tutorials, you need to be able to run Jupyter Notebook. See the installation guide for more information.

  • If you want to run R script tutorials, you need to be able to run Rstudio. See the installation guide for more information.

  • You need to have a UbiOps account. You can create a free account here.

UI tutorials

steps-overview The UI tutorials show how to set up your deployment package for typical use cases. You can download the deployment package, fill in the deployment creation form in the UI, and upload the deployment package. Afterwards you can make a request to the deployment to test it out.

Tutorials

steps-overview

Every tutorial contains a standalone example with all the material you need to run it. They are all centered around a Jupyter Notebook or Rstudio script. If you download the tutorial folder and run the notebook/script it will build the example in your own UbiOps account.

The current Python Tutorials

Topic and link to tutorial Functionalities of UbiOps addressed
Creating a training and production pipeline with Scikit Learn in UbiOps Deployments, pipelines
Deploying a TensorFlow model in UbiOps Deployments
Deploying an XGBoost model in UbiOps Deployments
Convert your MLFlow model to UbiOps deployment Deployments
Training a Tensorflow model Training
Training an XGBoost model Training
Checkpointing TensorFlow model training in UbiOps Training
Retraining a PyTorch model in UbiOps Training, Logs
Triggering a deployment/pipeline request from Azure Functions Different forms of requests, integration
Triggering a deployment/pipeline request from Google Cloud Functions Different forms of requests, integration
Azure Data Factory and UbiOps pipeline interaction tutorial Integration, pipelines
Using Azure ML services to train a model and deploy on UbiOps Integration, deployments
Pipeline that matches, orders and visualises a list of Pokemon Pipelines
Combining R and Python in the same pipeline: the prediction of house prices Deployments, pipelines
RFM analysis for Google Sheets with a pipeline Pipelines, Requests, Environment vars
How to turn your deployment into a live web app using Streamlit Deployments, Integration
Using TensorRT in Ubiops Deployments, Integration, Requests
Accelerate workflows with NVIDIA RAPIDS Local testing, Environments, Training
Huggingface & BERT Deployments, Integration, Requests, GenAI
Huggingface & Stable Diffusion Deployments, Integration, Requests, GenAI
Fine-tuning Falcon Training, Integration, GenAI

The current R Tutorials

Topic and link to tutorial Functionalities of UbiOps addressed
Combining R and Python in the same pipeline: the prediction of house prices Deployments, pipelines
Deploying an XGboost model Deployments
Deploying an R XGboost pipeline Deployments, pipelines

Requirements

To be able to use the UbiOps tutorials you need three things:

  • You need to have the UbiOps client library installed. For Python this can be done via pip install or via Setuptools. For more information see our GitHub Python page. For R this can be done by installing the devtools package and then using the install_github function. For more information see our GitHub R page

  • If you want to run Python tutorials, you need to be able to run Jupyter Notebook. See the installation guide for more information.

  • If you want to run R script tutorials, you need to be able to run Rstudio. See the installation guide for more information.

  • You need to have a UbiOps account. You can create a free account here.

*You might need to make some space in your project by deleting deployment versions if you want to run all the examples and stay within the limits of your account.