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: develop model in team environment, train the model with all the data on a Hadoop cluster, deploy model into production. The model will be a Spark ML model
Practical ML Topic – More details coming soon
• Networks and Pizza
– 6:30- 7:00 PM
• Why Data Science on Big Data?
Robert Hryniewicz – Hortonworks Data Science Evangelist
Huzefa Hakim – IBM Data Science Experience Product Manager
• Data Science at Scale Demo
Vikram Murali – IBM Data Science Experience Development Leader
Sriram Srinivasan – IBM Data Science Experience Architect
• Practical ML Topic
Robert Hryniewicz has over ten 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.