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  4. Data Driven Action: A Spring Primer on Data Science

Data Driven Action: A Spring Primer on Data Science

Learn some of the basics around data wrangling and NLP through Spring Java ecosystem.

Pieter Humphrey user avatar by
Pieter Humphrey
CORE ·
Jan. 10, 16 · Presentation
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In all industries, as software is eating the world, data is feeding software. However, to truly get value out of the data being generated, it must be analyzed and made actionable. Transformation in many industries actually means precisely this, data-driven action. From creating new television shows, to smart devices that help make your life easy, save precious limited resources, or protect your health, ingesting the data and building models are crucial to success.

This session will focus on examples of how these models are built. What is required to build a model? How does data need to be processed? What do you have to consider to make your model effective? And finally what tools do I use to build these models?

In this session, we will address these questions through illustrative use cases using open-source technologies varying from medical, text and sensor data, from three different speakers:

- Approaches and Open Source Tools for Wrangling and Modeling Massive Datasets

- Scaling Java Applications for NLP on MPP through PL/Java

- A Scalable Framework For Realtime Monitoring & Prediction Of Sensor Readings


Recorded at SpringOne2GX 2015.

Track: Big Data

Speakers: Sarah Aerni, Srivatsan Ramanujam, Jarrod Vawdrey

Slides: http://www.slideshare.net/SpringCentral/data-driven-action-a-primer-on-data-science

Data science Big data

Published at DZone with permission of Pieter Humphrey, DZone MVB. See the original article here.

Opinions expressed by DZone contributors are their own.

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  • Data Warehouses: The Undying Titans of Information Storage
  • Ethical AI and Responsible Data Science: What Can Developers Do?
  • Explainable AI: Making the Black Box Transparent
  • How to Sell Data Analytics to Non-Data Scientists

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