The best way to learn is to try it out yourself. Here you'll find our tutorials and use cases ready to be used by you. The tutorials will give you an overview of the platform or will highlight a specific feature.
We recommend you start with the Deploy an operational AI model tutorial. It will give you an overview of the platform's key concepts.
Explore how to build an image classification model that can recgonize handwritten numbers. Then deploy and test it.
Build and train an AI model with real data — both numbers and images — using the Peltarion Platform to make it reliable for house price prediction.
Build an image classifier of clothing through creating the typical building blocks of a convolution neural network.
Learn how to preprocess a dataset. Build, train, and deploy a model on the Peltarion Platform. Then create a web app to figure out if a song is pop or rock.
Use BERT to build a text classifier to perform sentiment analysis on movie reviews.
Solve a multi-label classification problem for content-based automatic music tagging.
A text similarity end-to-end project to figure out which of the old classic writing style you mirror.
Do some DNA research. Use multi-label classification to predict the protein expression rate.
Use a pretrained snippet in a classification model designed to detect different types of car damage.
How to solve an image segmentation problem.
Create a model that identifies patterns in Slack messages and tell people if they posted in the wrong channel.
Kaggle without knowing TensorFlow or PyTorch? In this tutorial we explore how it's possible.
Use an autoencoder to reconstruct noisy images.
Use BERT to build a text classifier for book summaries
