Our mission at Turi is to build the most powerful and usable data science tools that enable you to go quickly from inspiration to production.

GraphLab Create is a Python package that allows programmers to perform end-to-end large-scale data analysis and data product development.

• Data ingestion and cleaning with SFrames. SFrame is an efficient disk-based tabular data structure that is not limited by RAM. This lets you scale your analysis and data processing to handle terabytes of data, even on your laptop.

• Data exploration and visualization with GraphLab Canvas. GraphLab Canvas is a browser-based interactive GUI that allows you to explore tabular data, summary plots and statistics.

• Network analysis with SGraph. SGraph is a disk-based graph data structure that stores vertices and edges in SFrames.

• Predictive model development with machine learning toolkits. GraphLab Create includes several toolkits for quick prototyping with fast, scalable algorithms.

• Production automation with data pipelines. Data pipelines allow you to assemble reusable code tasks into jobs and automatically run them on common execution environments (e.g. Amazon Web Services, Hadoop).

In this guide, you will learn how to use GraphLab Create to:

• munge and explore both structured and unstructured data
• use advanced machine learning methods to build predictive models and recommender systems
• put your code into production and use it for real-world applications

The source for this userguide is available on Github under the 3-clause BSD license.

To build the userguide, install npm and run the following:

npm install
npm run gitbook-dep
npm run gitbook

The generated html will be located at _book/index.html.