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Featured resources

Data science community

Harness the power of the community. Check out the collection of articles, data sets, notebooks and tutorials.

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Github repository

A repository of demos, tutorials, sample apps and more.

Check out the resources (link resides outside ibm.com)

Stack Overflow

Common questions and answers about IBM Watson® Studio.

Search for answers (link resides outside ibm.com)

Forrester study

Forrester Consulting’s Total Economic Impact study quantifies the benefits of deploying Watson™ Studio and Watson Knowledge Catalog.

Download the study

Documentation

Explore more of what you can see and do with Watson Studio and see videos of key tasks.

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Solution brief

Find out how you can use this integrated platform designed to help data scientists and business analysts develop, train and manage models.

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Demos

Introduction to IBM Watson Studio Desktop

See how to start preparing data and building models on your desktop with visual drag-and-drop tools.

Watch the video (6:56)

Neural network modeler and deep-learning experiments

Get an overview of the neural network modeler tool and see how quickly a model can be created using this tool.

Watch the video (3:05)

Model management and deployment

Watson Studio allows data scientists and analysts to quickly build and prototype models, monitor deployments, and learn over time as more data becomes available.

Watch the video (2:49)

Build a logistic regression model

See how easy it is to build a logical regression model using the tooling available in Watson Studio.

Watch the video (4:03)

Watson Studio Local - Administration

See the introduction of Watson Studio Local administrative dashboard and community features.

Watch the video (5:39)

Watson Studio Local - Analytics

See the introduction of Watson Studio Local model builder and analytic asset features.

Watch the video (6:28)

Product tours and hands-on labs

IBM Watson Studio product tour: Create a machine-learning model to predict customer churn

Get experience with Watson Studio by creating a decision tree machine learning model to evaluate the risk of a customer leaving your service.

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IBM Watson Studio: Machine learning and deep learning made easy

Learn how to pick the best model for churn prediction and take advantage of Watson services.

Try the hands-on lab

IBM Watson Studio Modeler Flows product tour: Create an SPSS machine-learning model

Use Watson Studio Modeler Flows and the IBM SPSS® runtime to create a machine-learning model that evaluates customer churn risk and programmatically scores records.

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Speed up machine-learning and deep-learning development with modeler flows

Learn how to create modeler flows for three runtime environments: SPSS, Apache Spark, and Spark for Neural Networks.

Try the hands-on lab

IBM Watson Studio product tour: Create and test a visual recognition model

This product tour demonstrates how easy it is for all enterprises, big and small, to access visual recognition.

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IBM Watson Studio Local product tour: Build, train and deploy machine-learning models without coding

Take this product tour to learn how to train and deploy a machine-learning model, with no need for coding or manual model-building skills.

Explore the product tour

Installed Watson Studio? Check out these tutorials and use cases to learn more about the product.

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™.

Go to the tutorial

Build, deploy, test and retrain a predictive machine learning model

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.

Go to the tutorial

Analyze and visualize open data with Apache Spark

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Get started on Watson Studio in minutes

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