A Jupyter notebook using some standard techniques for data science and data engineering to analyze data for the 2017 flooding in Houston, TX.

This project walks through how you can create recommendations using Apache Spark machine learning. There are a number of jupyter notebooks that you can run on IBM Data Science Experience, and there a live demo of a movie recommendation web application you can interact with. The demo also uses IBM Message Hub (kafka) to push application events to…

Augment IBM Watson Natural Language Understanding APIs with a configurable mechanism for text classification, uses Watson Studio.

This journey helps to build a complete end-to-end analytics solution using IBM Watson Studio. This repository contains instructions to create a custom web interface to trigger the execution of Python code in Jupyter Notebook and visualise the response from Jupyter Notebook on IBM Watson Studio.

A pattern focusing on how to use scikit learn and python in Watson Studio to predict opioid prescribers based off of a 2014 kaggle dataset.

Mods for GTA V and RDR 2 to add support for adaptive triggers to the DualSense controller via DSX

Stream data from a Java program and use a Jupyter notebook to demonstrate charting of statistics based on historical and live events. IBM Db2 Event Store is used as the event database.

Get insights from OrientDB database using PyOrient through IBM Watson Studio

A collection of resources to facilitate your journey into data science

DSX trading bot example

Tools built to help work with Python notebooks in Data Science Experience

IBM Cloud Streaming Demo

Apache MXnet running in Apache Zeppelin and in DSX Jupyter

Build a model using Watson Machine Learning on Data Science Experience, running on IBM Cloud.

How to get started with IBM's Data Science Experience

Hands on Introduction to Apache Spark, ML, SPSS Modeler, Operationalizing Models, and Decision Optimization for Data Engineers, Data Scientist and Developers

Load, analyze and visualize public health violation data to uncover interesting insights about New York Restaurants using Apache Spark, Python and Jupyter