Layer Example Projects

This repository contains example projects that you can use to get started with Layer.

Layer is a collaborative MLOps platform where you can build, train, version and share your machine learning (ML) models.

Install Layer

The first step is to install Layer:

pip install layer

Clone the examples repository

The first step is to clone this repository:

git clone https://github.com/layerai/examples

Select an example project

Next, select one example project and change into that folder. Let's use the Titanic example for illustration:

cd examples/titanic

Open the associated notebook or Python script and run it. Layer runs your project and places the generated entities in the appropriate Discover tabs.

Use the generated entities in a Jupyter Notebook

Entities generated with Layer can also be accessed in a Jupyter Notebook. Layer allows you to access the datasets, feature sets, and models.

First, let's look at how to access the created datasets:

import layer
dataset = layer.get_dataset('layer/titanic/datasets/passengers')

The model can be accessed using Layer get_model function:

import layer
model = layer.get_model('layer/titanic/models/survival_model')

The model can be used to make predictions right away:

df = layer.get_dataset("passengers").to_pandas()
passenger = df[['Pclass', 'Sex', 'Age', 'SibSp', 'Parch', 'Fare']]
survival_probability = model.get_train().predict_proba(passenger.sample())[0][1]
print(f"Survival Probability: {survival_probability:.2%}")

# > Survival Probability: 68.37%

Next steps

To learn more about using layer, you can: