To help our audience leverage the power of machine learning, the editors of insideBIGDATA have created this weekly article series called “The insideBIGDATA Guide to Machine Learning.” This is our sixth installment, “Unsupervised Machine Learning.”
Deep learning is a new force in the field of data science – a set of algorithms in machine learning that attempt to model high-level abstractions in data by using architectures composed of multiple non-linear transformations. The talk below breaks the ice for those not familiar with this technology. This talk was presented at the SF Neural Network Aficionados Discussion Group hosted by NextSpace in San Francisco.
“Some c-suite executives have quickly discovered the power of analytics, while others were more reluctant to embrace it. We see companies that embrace analytics across the enterprise as being more successful than their competitors. These observations have also been supported by academic studies that conclude that analytic oriented and metric driven organizations outperform those that do not embrace analytics holistically.”
Seventy-five percent of businesses have yet to successfully deploy big data analytics solutions to gain business-impacting insights, despite 65 percent increasing their investment in analytic services and technologies in 2014. These findings are part of “Analytics 2014,” Lavastorm’s second annual survey on analytic usage, trends, and future initiatives.
A very hot topic in data science these days is the ability to discern “sentiment” by analyzing text from social media sources. In the talk below, Ryan Rosario presents some of his work at Facebook – “Sentiment Classification Using scikit-learn.” Ryan is a Quantitative Engineer at Facebook.
“AgilOne is a cloud-based predictive marketing platform that makes advanced analytics and predictive targeting easy for all marketers large and small. We believe all marketers have the right to deliver happiness. Unlike offerings from large vendors such as IBM and Adobe, AgilOne is easy to install and easy to use. It is the only integrated platform that combines data integration (omni-channel customer profiles) with advanced predictive analytics and out of the box predictive marketing campaigns (actions).”
For up-and-coming data scientists who need to get up to speed on Hadoop architectures, here is another in a long line of compelling Big Data & Brews episodes. In the video below we hear from three Hadoop luminaries about the Hadoop projects they’ve worked on – Erich Nachbar on Spark, Michael Stack on Hbase and Ari Zilka (from Hortonworks) on Stinger. Great insider’s perspective!
One of the attractions of the Hadoop Summit 2014 was the Big Data & Brews interview series – “Live from Hadoop Summit.” These short, well-focused discussions always provide good light into important industry trends. In the episode below, the conversation turns to the subject of SQL on Hadoop. Stefan Groschupf, the CEO of Datameer, recorded a special interview with Ovum analyst Tony Baer who gave his thoughts on the topic.
“With a novel data analytics approach, Mellanox is providing double performance to data Extract, Transform, Load (ETL) solutions based on Hadoop Map Reduce. The code to enable such performance gains is part of the Hadoop community code. With acceleration of the networking stack, Mellanox is quadrupling the number of clients served on a single Memcached server, a dominating key-value caching service for large scale web applications.”
Feeling left out because your boss wouldn’t let you attend the Hadoop Summit 2014 happening this week? Not to worry! Here’s a free alternative, especially attractive if you happen to live/work in Los Angeles. The Big Data Camp LA 2014 is a free, all-day conference on Saturday, June 14 hosted at the DirectTV campus near LAX.