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Introduction

Let’s look at some examples of how you can use Layer for different use cases. All of the examples can be found in our public repo: https://github.com/layerml/examples

Titanic Survival Model#

A classification example with sklearn.RandomForestClassifier for predicting the survivals of the Titanic passengers. We will be using the famous Kaggle Titanic dataset.

layer clone https://github.com/layerml/examples
cd examples/titanic

Fraud Detection#

A gradient boosting example with xgboost library to reveal suspicious transactions. We will be working with a transaction log dataset from Synthetic Financial Datasets For Fraud Detection

layer clone https://github.com/layerml/examples
cd examples/fraud-detection

Hyperparameter Tuning Example#

Layer provides a declarative way of Hyperparameter Tuning. We will tune the parameters of Titanic Survival Model to find the best configuration. We will see how we can use different search algorithms: Random, Bayesian, Manual and Grid.

layer clone https://github.com/layerml/examples
cd examples/titanic-hyperparametertuning

Spam Detection#

An NLP example with nltk library to predict the spam sms messages. In this project, we are going to use Python Features to remove stop words and lemmatize messages.

layer clone https://github.com/layerml/examples
cd examples/spam-detection