Building a Machine Learning Engine from Big Data

Posted by Aashish Majethia on Dec 9, 2016 8:11:10 AM

Machine learning (ML) is still growing as a field in big data and has of late made some significant advances. In fact, practical applications have become quite commonplace and most of us have benefited from it already. Email providers use it to determine whether an email is spam or legitimate. Credit card companies use it to flag potentially fraudulent charges. Hospitals are using it to improve outcomes for patients. If you’re a Netflix customer, you may have even been suggested a movie using machine learning :-)  It’s obviously a hot topic and is making it’s way across newer industries as capabilities grow. A simple ‘machine learning’ search on Amazon returns over 13,000 books.

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Topics: Hadoop, Big Data Ecosystem, Data Science, Bedrock, Machine Learning

Machine Learning: How to Master the Basics and Transform your Dataset

Posted by Jean Georges Perrin on Sep 28, 2016 9:18:56 AM

You might be familiar with various number puzzles on LinkedIn. Although some might complain about how they disrupt their LinkedIn news feed (e.g. “This isn’t Facebook!”), the puzzles are designed to trigger your intelligence or challenge your neurons.

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Topics: Data Science, Machine Learning

Why You’re Not Getting the ROI You Expected from Data Science

Posted by Satish Vutukuru on May 19, 2016 2:11:35 PM

Although many enterprises are beginning to heavily invest in data science activities, only a handful of them are seeing the desired ROI. That’s because it’s hard to do. It’s difficult to shift to a culture of building and scaling data-driven services and products. It’s a challenge to operationalize data science processes and integrate data science into business practices. It’s an uphill battle to put an enterprise’s data “house” in order, to get a complete view of what data exists and eliminate data silos and connect disjointed analytics teams. All of these challenges are among the reasons why most enterprises aren’t getting the return they expected from their data science investments.

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Topics: Data Science

The Managed Data Lake: A Strong Foundation for Data Science

Posted by Satish Vutukuru on May 11, 2016 2:21:27 PM

 What is Data Science?  The jury is still out on a precise definition. This probably has to do with the reality that the field is constantly evolving as the types of data and the tools we have to extract value from data also evolve. A Booz Allen Hamilton guide says that data science is about turning data into action and delivering this actionable intelligence in an understandable way to business end users. Data science pioneers Thomas H. Davenport and D.J. Patil aptly described the iterative nature of data science in a Harvard Business Review blog post, stating “data scientists help decision makers shift from ad hoc analysis to an ongoing conversation with data.” Others specify that unlike business intelligence, data science uses complex algorithms and machine-learning/predictive analytics to not only look for answers, but discover new questions to ask.

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Topics: Data Science