Data science holds tremendous potential for organizations to uncover new insights and drivers of revenue and profitability. Big Data has brought the promise of doing data science at scale to enterprises, however this promise also comes with challenges for data scientists to continuously learn and collaborate. Data Scientists have many tools at their disposal such as notebooks like Juypter and Apache Zeppelin & IDEs such as RStudio with languages like R, Python, Scala and frameworks like Apache Spark. Given all the choices how do you best collaborate to build your model and then work through the development lifecycle to deploy it from test into production?
Why Data Science on Big Data?
In this meetup you will cover the attributes of a modern data science platform that empowers data scientists to build models using all the data in their data lake and foster continuous learning and collaboration. We will show a demo of Apache Zeppelin, Apache Spark, Apache Livy and Apache Hadoop with the focus on integration, security and model deployment and management.
Data Science at Scale DEMO
The demo will cover the Data Science life cycle: developing models in a team environment, training the model with all the data on a Hadoop cluster, and deploying model into production. The model will be a Spark ML model.
• 18:30 – 19:00 – Networking
• 19:00 – 19:30 – Why Data Science on Big Data
• 19:30 ~ 20:00 – DSX* on HDP** demos
IoT Trucking Demo
Customer Churn Demo
Robert Hryniewicz has over 10 years working on various projects related to Artificial Intelligence, Enterprise Software, IoT, Robotics and more. Currently, he’s a Data Scientist and Evangelist at Hortonworks. Previously, Robert was a CTO at a Singularity Labs startup, Sr. Architect at Cisco, NASA et al. He’s a frequent speaker at DataWorks / Hadoop Summits.
Other speakers TBD