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Build, deploy, test and retrain a predictive machine learning model
This tutorial walks you through the process of building a predictive machine learning model, deploying it as an API to be used in applications, testing it, and retraining it with feedback data. All of this happens in an integrated and unified self-service experience on IBM Cloud™.
Analyze and visualize open data with Apache Spark and Watson Studio
In this tutorial, you will analyze and visualize open data sets using a Jupyter notebook on Watson Studio, with Apache Spark for processing. For this use case, you will start by combining data about population growth, life expectancy and country ISO codes into a single data frame. Then, query and visualize that data in several ways using the Pixiedust library for Python.
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Explore Watson Studio Local
Take a product tour to learn how to prepare a data set, train and evaluate a model, create a decision tree and more.