# Tutorials and Examples
To help you get started we've put together a collection of tutorials for various features in cnvrg. On this page, you can access all of the tutorials.
# Example Projects
- Build and Deploy an IMDB NLP Model
- Train and Deploy a CNN for MNIST
- Use R to Train an Iris Classification Model
- Approximate Pi using Spark on Kubernetes
- Publish a Dash App using Facets
- Publish an R Shiny App using Iris
# Workspaces, Experiments and IDEs
- Run an Experiment in a Jupyter Workspace
- Using Pycharm with cnvrg
- Convert and Run Python Notebooks using nbconvert
- View and compare Jupyter Notebooks
- Monitor your Experiment's Health
- Advanced Model Tracking with Keras Callbacks
- Advanced Model Tracking in PyTorch
- R Experiment Tracking
- Advanced Model Tracking in PyTorch Lighning
- Custom R Shiny Example
- Remote SSH in Visual Studio Code
- Remote Python Interpreter in PyCharm
- Remote Python Interpreter in IntelliJ IDEA
- Run a Distributed Tensorflow Experiment using Horovod and MPI
- Run Hyperparameters tuning using Ray
# Flows and Serving
- Processing your Dataset with Flows
- Create a Simple Flow with Two Tasks
- Build a Canary Release Flow
- Setup and Make a Batch Prediction
- Monitor, Retrain and Learn from your cnvrg Endpoint