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