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 to start with the Deploy an operational AI model tutorial. It will give you an idea of the platform key concepts.

01/ Deploy an operational AI model This tutorial will show you how to build a model that will solve a classification problem.
02/ Predict California house prices This is a regression problem where you want to predict a quantity, in this case, the price of a house.
03/ Classifying images of clothes Build an image classifier of clothing through creating the typical building blocks of a convolution neural network.
04/ Movie review sentiment analysis Build a text classifier to perform sentiment analysis on movie reviews.
05/ Predicting mood from raw audio data Solve a multi-label classification problem for content-based automatic music tagging.
06/ Gene expression prediction This is a regression problem where you will predict the protein expression rate for a given DNA sequence.
07/ Classifying car damages Use a pretrained snippet in a classification model designed to detect different types of car damages.
08/ Skin lesion segmentation How to solve an image segmentation problem.
09/ Participating in a Kaggle competition with zero code How to work with exported models.
10/ Denoising images Use an autoencoder to reconstruct noisy images.
11/ Classifying fruits How to do an off-platform analysis of a classifier model.

Platform tutorials

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