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Perform a machine learning exercise

Dive into machine learning by performing an exercise on IBM Data Science Experience using Apache SystemML.


Build a recommender with Apache Spark and Elasticsearch

This developer pattern demonstrates the key elements of creating a recommender system by using Apache Spark and Elasticsearch.


Robotic calculations and inference agent

This journey takes you through end to end flow of steps in building an interactive interface between NAO Robot, Watson Conversation API & Data Science Experience


Correlate documents

Correlate content across documents using Python NLTK, Watson Natural Language Understanding (NLU) and IBM Data Science Experience (DSX)


Orchestrate data science workflows using Node-RED

Build a web interface using Node-RED to trigger an analytics workflow on IBM Data Science Experience.


Extend Watson text classification

Augment classification of text from Watson Natural Language Understanding with IBM Data Science Experience.


Detect change points in IoT sensor data

Use time series from IoT sensor data, IBM Data Science Experience, and the R statistical computing project to analyze the data and detect change points.


Discover hidden Facebook usage insights

Enrich unstructured data from Facebook using a Jupyter Notebook with Watson Visual Recognition, Natural Language Understanding, and Tone Analyzer, then use PixieDust to explore the results and uncover hidden insights.


Analyze traffic data from the city of San Francisco

Look at traffic data from the city of San Francisco, create robust data visualizations that allow users to encapsulate business logic, create charts and graphs, and quickly iterate through changes in the notebook.


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Analyze traffic data from the city of San Francisco

In this developer journey, we will use PixieDust running on IBM Data Science Experience to analyze traffic data from the city of San Francisco. Data is claimed to be the most valuable commodity in the world. At IBM, we want you to take advantage of your data – manipulate it, visualize it, and understand it...

Continue reading Analyze traffic data from the city of San Francisco

Leverage the Data Science Experience to analyze StarCraft II replays

It comes as no surprise that studies show more than 70 percent of American households play video games. What might surprise you is that there are 1.8 billion gamers worldwide! While it’s hard to explain the appeal to some, it is speculated that video games fill a human void in a way that our world...

Continue reading Leverage the Data Science Experience to analyze StarCraft II replays

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