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

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.

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…

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.

Apache MXnet running in Apache Zeppelin and in DSX Jupyter

Watson Data Platform Quick Start guide + Data Science Experience Hands-on

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

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

Hands on Introduction to Apache Spark, NLP, ML and Operationalizing Models for Data Engineers, Data Scientist and Developers