Machine Learning Times
Machine Learning Times
EXCLUSIVE HIGHLIGHTS
Three Best Practices for Unilever’s Global Analytics Initiatives
    This article from Morgan Vawter, Global Vice...
Getting Machine Learning Projects from Idea to Execution
 Originally published in Harvard Business Review Machine learning might...
Eric Siegel on Bloomberg Businessweek
  Listen to Eric Siegel, former Columbia University Professor,...
Effective Machine Learning Needs Leadership — Not AI Hype
 Originally published in BigThink, Feb 12, 2024.  Excerpted from The...

Hadoop

Opportunities and Challenges: Predictive Analytics for IoT

 There is a clear sense in the marketplace today that for the internet of things (IoT) to realize its true potential as the next-big-thing, analytics is going to be critical. After all what is the purpose of connecting all these devices and gathering the data if we are not going to do anything about it? (more…)

Predictive Analytics, Cognitive computing & Algorithms: 10 Big Data Predictions for 2016

 List: Find out what to expect from big data in 2016 from some of the top minds in the tech industry – SAP, Salesforce, Teradata, HPE and many more. It is the season for predictions, so CBR...

Hadoop in Banking: Changing the Game

 The reason for Hadoop’s success in the banking and finance domain is its ability to address various issues faced by the financial industry at minimal cost and time. Despite the various benefits of Hadoop, to apply it...

The Ultimate Guide to Data Science Blogs

 We’ve organized data science blogs across eight different categories: Machine learning, Hadoop, R, Python, business intelligence, data visualization, statistics, and a general data science bucket. Data about their reader count comes from Feedly. This is a work...

Choosing the Right Vendor for your Big Data Needs

 Choosing the right vendor for managing Big Data requires each organization to consider its own needs, including preferences related to data storage, scripting language, and preferred usage tools. USE CODE PATIMES16 for 15% off Predictive Analytics World...

Oracle’s Ten Enterprise Big Data Predictions for 2016

 Companies big and small are finding new ways to capture and use more data. The push to make big data more mainstream will get stronger in 2016. Here are Oracle’s top 10 predictions: 1. Data civilians operate more...

Your Big Data Strategy is a Bust

 If big data has reached a point where it has simply become essential to everything else, why are so many companies still struggling to put their data to good use? The big data furniture Big data used...

The Making of a Modern Data Scientist

 The world is churning out 2.5 quintillion bytes of data every day, with 90% of it created in the past two years. Most of this staggering volume comes from apps, social media sites, YouTube and other video...

Taking the Mystery Out of Big Data

 Today’s companies have the potential to benefit from incredibly large amounts of data. To shake off the mystery of this “Big Data,” it’s useful to know its history. In the not-so-distant past, firms tracked their own internal...

Spark And Hadoop Are Friends, Not Foes

 June was an exciting month for Apache Spark. At Hadoop Summit San Jose, it was a frequent topic of conversation, as well as the subject of many session presentations. On June 15, IBM announced plans to make a massive...

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