--- title: "Opera Solutions' Blog: The Hottest Spot for Practical AI and Big Data Science | Machine Learning (2)" description: Machine Learning | Opera Solutions is the largest independent predictive analytics company in the world, providing Practical AI and Big Data Analytics as an ongoing service to blue-chip clients across the globe. (2) --- [![](https://blog.operasolutions.com/hs-fs/hubfs/Opera_Solutions_Logo_Standard_RGB-72.png?width=369&height=202&name=Opera_Solutions_Logo_Standard_RGB-72.png "Opera_Solutions_Logo_Standard_RGB-72.png")](https://www.operasolutions.com/) ![Blog_Header-4](https://blog.operasolutions.com/hs-fs/hubfs/Blog_Header-4.png?width=3377&name=Blog_Header-4.png "Blog_Header-4") [![Blog_Banner_v3](https://blog.operasolutions.com/hs-fs/hubfs/Blog_Banner_v3.png?width=3713&name=Blog_Banner_v3.png "Blog_Banner_v3")](https://blog.operasolutions.com) ## [Analytics in Healthcare: How to Survive the ICD-10 Transition](https://blog.operasolutions.com/analytics-in-healthcare-how-to-survive-the-icd-10-transition) Posted by [Sarah Anderson](https://blog.operasolutions.com/author/sarah-anderson) on Thu, Oct 01, 2015 - [Tweet](https://twitter.com/share) [![](https://blog.operasolutions.com/hubfs/OS_SignalCentral_ICD-10_GP_2015_V1.0-02.jpg)](https://blog.operasolutions.com/analytics-in-healthcare-how-to-survive-the-icd-10-transition) *Is now the right time to add machine-learning analytics into your charge-capture management system?* ICD-10 is here and chances are, as a provider, you’re as ready for it as you can be, knowing there could be some hiccups and impact on revenues. Most predict that the impact will be confined to inpatient revenues, driven by significant adjustment issues in grouper methodologies. But what if the impact extends well beyond that, to outpatient revenues? [Read More](https://blog.operasolutions.com/analytics-in-healthcare-how-to-survive-the-icd-10-transition) Topics: [Healthcare](https://blog.operasolutions.com/topic/healthcare), [Machine Learning](https://blog.operasolutions.com/topic/machine-learning) ## [My Struggle With Marketing Automation](https://blog.operasolutions.com/bid/390322/My-Struggle-With-Marketing-Automation) Posted by [Todd Higginson](https://blog.operasolutions.com/author/todd-higginson) on Mon, Jun 30, 2014 - [Tweet](https://twitter.com/share) [![](https://blog.operasolutions.com/hs-fs/file-1106290924-jpg/images/wheels.jpg)](https://blog.operasolutions.com/bid/390322/My-Struggle-With-Marketing-Automation) *Marketing automation's time has finally come, but it's been a long, tortuous road.* I’m a big fan of marketing automation. My experience goes back a few years. I was just getting settled at a new company when our CFO received a renewal invoice from a marketing automation vendor. She didn’t know how we were using the software, and neither did I.  [Read More](https://blog.operasolutions.com/bid/390322/My-Struggle-With-Marketing-Automation) Topics: [Big Data](https://blog.operasolutions.com/topic/big-data), [Machine Learning](https://blog.operasolutions.com/topic/machine-learning), [Marketing](https://blog.operasolutions.com/topic/marketing) ## [The 5 Best Data Science Tools from the 2014 Hadoop Summit](https://blog.operasolutions.com/bid/389599/the-5-best-data-science-tools-from-the-2014-hadoop-summit) Posted by [Daniel D. Gutierrez](https://blog.operasolutions.com/author/daniel-d-gutierrez) on Fri, Jun 20, 2014 - [Tweet](https://twitter.com/share) [![](https://blog.operasolutions.com/hs-fs/file-1052968212-jpg/images/hadoop_summit.jpg)](https://blog.operasolutions.com/bid/389599/the-5-best-data-science-tools-from-the-2014-hadoop-summit) The [Hadoop Summit](http://hadoopsummit.org/san-jose/) conference, hosted by Hortonworks and Yahoo, has become a must-see Big Data event. The Hadoop distributed computing architecture is now an integral part of what it means to be a data scientist, and a few days of concentrated effort each year is enough to get a vision for where the industry is headed. The Hadoop Summit serves this purpose well by providing thought-provoking technical sessions, keynote addresses, and a vendor exhibition that brings many of the major players in the Hadoop ecosystem together under one roof. [Read More](https://blog.operasolutions.com/bid/389599/the-5-best-data-science-tools-from-the-2014-hadoop-summit) Topics: [Data Science](https://blog.operasolutions.com/topic/data-science), [Machine Learning](https://blog.operasolutions.com/topic/machine-learning), [Events](https://blog.operasolutions.com/topic/events) ## [Data Science As the Panacea for Healthcare Fraud, Waste, and Abuse](https://blog.operasolutions.com/bid/388511/data-science-as-the-panacea-for-healthcare-fraud-waste-and-abuse) Posted by [Daniel D. Gutierrez](https://blog.operasolutions.com/author/daniel-d-gutierrez) on Thu, Jun 12, 2014 - [Tweet](https://twitter.com/share) [![](https://blog.operasolutions.com/hs-fs/file-981521063-jpg/images/os_signalcentral-healthcare-fraud_gp_2041_v1.0-02-300.jpg)](https://blog.operasolutions.com/bid/388511/data-science-as-the-panacea-for-healthcare-fraud-waste-and-abuse) *Edited by [Yan Zhang](mailto:yzhang2@operasolutions.com)* Many pundits speaking about the state of the nation’s healthcare infrastructure routinely point to fraud, waste, and abuse (FWA) as major reasons for many of the problems the public witnesses every day – increased healthcare costs and the resulting increase in insurance premiums. The net effect is an annual loss of billions of dollars, and these losses affect the public in very real ways.  The size of the healthcare sector, the enormous amount of money involved, and the lack of surveillance and monitoring mechanisms across the healthcare ecosystem make it an attractive target for FWA. According to the Office of Management and Budget, in 2010, about 9%, or [$47.9 billion](http://www.politifact.com/truth-o-meter/statements/2011/jan/04/darrell-issa/rep-darrell-issa-claims-government-could-save-125-/) was lost to fraud in Medicare alone. It is therefore imperative to develop effective FWA technologies and solutions for reducing the costs associated with our healthcare system. Data science and its primary enabling methodology of machine learning represent the country’s best chance for detecting FWA to avoid extraordinary sources of loss. Data science possesses the facilities to make a significant difference healthcare industry budgets and their impact to the public. Opera Solutions is the industry leader in applying Big Data technologies to the most challenging and significant business problems. We are the company charged with developing the analytics to identify fraud for the Centers for Medicare & Medicaid Services (CMS) on the health insurance exchanges. Here’s a look into just how big this challenge is — and some of the approaches we’re taking to overcome one of the costliest burdens in America. [Read More](https://blog.operasolutions.com/bid/388511/data-science-as-the-panacea-for-healthcare-fraud-waste-and-abuse) Topics: [Healthcare](https://blog.operasolutions.com/topic/healthcare), [Big Data](https://blog.operasolutions.com/topic/big-data), [Data Science](https://blog.operasolutions.com/topic/data-science), [Machine Learning](https://blog.operasolutions.com/topic/machine-learning) ## [What Is Data Science?](https://blog.operasolutions.com/bid/384900/what-is-data-science) Posted by [Daniel D. Gutierrez](https://blog.operasolutions.com/author/daniel-d-gutierrez) on Tue, May 06, 2014 - [Tweet](https://twitter.com/share) [![](https://blog.operasolutions.com/hs-fs/file-727132374-jpg/images/os_signalcentral-what-is-data-science_gp_2014_b-small1.jpg)](https://blog.operasolutions.com/bid/384900/what-is-data-science) As a relatively new term, “data science” can mean different things to different people due in part to all the hype surrounding the field. Often used in the same breath, we also hear a lot about “big data” and how it is changing the way that companies interact with their customers. This begs the question — how are these two technologies related? Unfortunately, the hype can cloud our understanding for how these technologies are working to shape our increasingly data-driven society. Rest assured, there truly is something deep and profound representing a paradigm shift in our society surrounding data, but the hype isn’t helping to clarify data science’s exact role in Big Data. In this article, we strive to put to rest many of the misunderstandings surrounding data science. [Read More](https://blog.operasolutions.com/bid/384900/what-is-data-science) Topics: [Data Science](https://blog.operasolutions.com/topic/data-science), [Machine Learning](https://blog.operasolutions.com/topic/machine-learning), [Analytics](https://blog.operasolutions.com/topic/analytics) ## [Data Science and ICD-10 Team Up to Benefit Healthcare](https://blog.operasolutions.com/bid/380558/data-science-and-icd-10-team-up-to-benefit-healthcare) Posted by [Daniel D. Gutierrez](https://blog.operasolutions.com/author/daniel-d-gutierrez) on Mon, Mar 31, 2014 - [Tweet](https://twitter.com/share) [![](https://blog.operasolutions.com/hs-fs/file-623970395-jpg/images/icd-graphic-v1.0-06.jpg)](https://blog.operasolutions.com/bid/380558/data-science-and-icd-10-team-up-to-benefit-healthcare) *Switching to a new medical coding system won’t be easy, but when combined with data science and machine learning, ICD-10 presents enormous potential benefits for both the financial and the clinical sides of healthcare.* Part of why the healthcare industry is such a notorious laggard in jumping on the Big Data bandwagon is that every attempted change faces a huge domino effect, rendering many good ideas useless until everyone — and everything — is ready. One big step in the right direction, however, is an important upgrade to the computerized codes used for *electronic medical records* (EMR), which will take hold in the next year or two. These codes, known as ICD or *International Classification of Diseases*, determine what ailments patients have and how much they and their insurers should pay for a treatment. The set of codes, currently called ICD-9, is scheduled for its 10th revision this fall (but there may be a year-long [delay](http://www.ihealthbeat.org/articles/2014/3/27/house-passes-doc-fix-that-includes-one-year-icd-10-delay)). The updated codes, called ICD-10 codes, improve on the previous standard by adding more descriptive capabilities that will help healthcare professionals better categorize and keep track of patient disorders and treatments. Through the use of machine learning and other data science techniques, this increased granularity is expected to open up patient treatment analytics along with the ability to better monitor public health threats. [Read More](https://blog.operasolutions.com/bid/380558/data-science-and-icd-10-team-up-to-benefit-healthcare) Topics: [Healthcare](https://blog.operasolutions.com/topic/healthcare), [Big Data](https://blog.operasolutions.com/topic/big-data), [Data Science](https://blog.operasolutions.com/topic/data-science), [Machine Learning](https://blog.operasolutions.com/topic/machine-learning) ## [How Machine Learning Will Affect Your Next Vacation](https://blog.operasolutions.com/bid/350568/how-machine-learning-will-affect-your-next-vacation) Posted by [Sarah Anderson](https://blog.operasolutions.com/author/sarah-anderson) on Wed, Dec 04, 2013 - [Tweet](https://twitter.com/share) [![](https://blog.operasolutions.com/hs-fs/file-379184941-jpg/images/vacation_suitcase.jpg)](https://blog.operasolutions.com/bid/350568/how-machine-learning-will-affect-your-next-vacation) *You may not be paying much attention to data science, but it’s paying attention to you — and will deliver personalized search results in due time.* For those of us who prefer to stay on the shopping side of recommender engines, how online retailers seem to know which hotels we’ll book, what flights we’ll take, or what brand of pots and pans we’ll buy next is simply *math*, or for those of us with a little more knowledge, *algorithms*. For most everyone else, it pretty much falls under something more akin to *science so advanced it might as well be magic*. Of course, for the machine learning data scientists who create these recommender engines, all engines are different, complex — and definitely not magic. [Read More](https://blog.operasolutions.com/bid/350568/how-machine-learning-will-affect-your-next-vacation) Topics: [Big Data](https://blog.operasolutions.com/topic/big-data), [Machine Learning](https://blog.operasolutions.com/topic/machine-learning), [Competitions](https://blog.operasolutions.com/topic/competitions) ## [Sentiment Analysis: English 101 for Computers](https://blog.operasolutions.com/bid/323464/sentiment-analysis-english-101-for-computers) Posted by [Brian Kolo, Ph.D., J.D.](https://blog.operasolutions.com/author/brian-kolo-phd-jd) on Thu, Aug 01, 2013 - [Tweet](https://twitter.com/share) [![](https://blog.operasolutions.com/hs-fs/file-241005202-jpg/images/word_cloud_3.jpg)](https://blog.operasolutions.com/bid/323464/sentiment-analysis-english-101-for-computers) *Think you know English? Think again. See if you have what it takes to teach a computer how to understand humans.* Anyone who has tried to learn English as a second language is only too familiar with its many — many — challenges. In addition to idioms, sarcasm, and a wide array of meanings when combined with various prepositions (think: *make up, make out, make it,* and of course, *makeup*), there’s also pop culture, trends, products, and more to keep straight. Luckily for us, we’re human, and even those well established in their native languages will be able to speak and decipher English with enough practice and exposure. But what about machines? How do we even begin to program them in a way that they can read and understand sentiment? Answer: very carefully. The process requires machine learning data scientists to use Natural Language Process (NLP) techniques, a form of advanced analytics. They use these techniques to build models that can decipher sentiment and weed out the meaningful information among the noise.  [Read More](https://blog.operasolutions.com/bid/323464/sentiment-analysis-english-101-for-computers) Topics: [Big Data](https://blog.operasolutions.com/topic/big-data), [Data Science](https://blog.operasolutions.com/topic/data-science), [Machine Learning](https://blog.operasolutions.com/topic/machine-learning), [Marketing](https://blog.operasolutions.com/topic/marketing) ## [Big Data Takes the Travel Industry in New Direction](https://blog.operasolutions.com/bid/311798/big-data-takes-the-travel-industry-in-new-direction) Posted by [Harry Shilling](https://blog.operasolutions.com/author/harry-shilling) on Thu, Jun 27, 2013 - [Tweet](https://twitter.com/share) [![](https://blog.operasolutions.com/hs-fs/file-208238747-jpg/images/luggage-carousel.jpg)](https://blog.operasolutions.com/bid/311798/big-data-takes-the-travel-industry-in-new-direction) *A new report, featured in* The New York Times*, highlights the benefits of Big Data and machine learning in the airline industry and beyond.* The travel industry has always been a vast data collector. Every airline reservation, every hotel booking, every car rental ends up in a conventional database of structured data. But today Big Data — the unstructured data that includes ratings on blog sites, likes on social media, conversations with call centers, customer clickstreams, and more — is becoming increasingly important in determining how travel companies keep customers coming back. [Read More](https://blog.operasolutions.com/bid/311798/big-data-takes-the-travel-industry-in-new-direction) Topics: [Big Data](https://blog.operasolutions.com/topic/big-data), [Machine Learning](https://blog.operasolutions.com/topic/machine-learning), [Signals](https://blog.operasolutions.com/topic/signals), [Marketing](https://blog.operasolutions.com/topic/marketing) ## [Opera CEO Explains Machine Learning on CNBC](https://blog.operasolutions.com/bid/270409/opera-ceo-explains-machine-learning-on-cnbc) Posted by [Sarah Anderson](https://blog.operasolutions.com/author/sarah-anderson) on Wed, Apr 24, 2013 - [Tweet](https://twitter.com/share) [![](https://blog.operasolutions.com/hs-fs/file-30959433-jpg/images/arnab_candid_photo.jpg)](https://blog.operasolutions.com/bid/270409/opera-ceo-explains-machine-learning-on-cnbc) *Opera Solutions’ Arnab Gupta explores the vast opportunities in Big Data on* CNBC’s “Squawk Box.” "The Big Data phenomenon is so vast, it can support 50 IBMs." That was just one of the thought-provoking statements Opera Solutions’ CEO, [Arnab Gupta](http://www.operasolutions.com/listings/arnab-gupta/), made during his appearance on CNBC’s “[Squawk Box](http://video.cnbc.com/gallery/?play=1&video=3000163539)” as he spoke with hosts Andrew Ross Sorkin, Becky Quick, and Joe Kernen on April 24th. [Read More](https://blog.operasolutions.com/bid/270409/opera-ceo-explains-machine-learning-on-cnbc) Topics: [Big Data](https://blog.operasolutions.com/topic/big-data), [Machine Learning](https://blog.operasolutions.com/topic/machine-learning), [Arnab Gupta](https://blog.operasolutions.com/topic/arnab-gupta) [Previous](https://blog.operasolutions.com/topic/machine-learning/page/1) [All posts](https://blog.operasolutions.com/all) [Next](https://blog.operasolutions.com/topic/machine-learning/page/3) ### Subscribe to Email Updates ### Recent Posts ### Posts by Topic - [Big Data (75)](https://blog.operasolutions.com/topic/big-data) - [Machine Learning (38)](https://blog.operasolutions.com/topic/machine-learning) - [Data Science (32)](https://blog.operasolutions.com/topic/data-science) - [Signal Hub Technologies (27)](https://blog.operasolutions.com/topic/signal-hub-technologies) - [Analytics (26)](https://blog.operasolutions.com/topic/analytics) - [Marketing (23)](https://blog.operasolutions.com/topic/marketing) - [Press Releases (22)](https://blog.operasolutions.com/topic/press-releases) - [Arnab Gupta (16)](https://blog.operasolutions.com/topic/arnab-gupta) - [Events (10)](https://blog.operasolutions.com/topic/events) - [Healthcare (10)](https://blog.operasolutions.com/topic/healthcare) - [Signals (10)](https://blog.operasolutions.com/topic/signals) - [Partners (8)](https://blog.operasolutions.com/topic/partners) - [Artificial Intelligence (7)](https://blog.operasolutions.com/topic/artificial-intelligence) - [Competitions (7)](https://blog.operasolutions.com/topic/competitions) - [Supply Chain & Operations (7)](https://blog.operasolutions.com/topic/supply-chain-operations) - [Videos (6)](https://blog.operasolutions.com/topic/videos) - [Mobiuss (5)](https://blog.operasolutions.com/topic/mobiuss) - [Security & Defense (4)](https://blog.operasolutions.com/topic/security-defense) - [Data Equity (3)](https://blog.operasolutions.com/topic/data-equity) - [Customer Yield Management (2)](https://blog.operasolutions.com/topic/customer-yield-management) - [Hadoop (2)](https://blog.operasolutions.com/topic/hadoop) - [OperaNotebook (2)](https://blog.operasolutions.com/topic/operanotebook) - [Practical AI (2)](https://blog.operasolutions.com/topic/practical-ai) - [SoftwareUpdates (2)](https://blog.operasolutions.com/topic/softwareupdates) - [Spark (2)](https://blog.operasolutions.com/topic/spark) - [Transformative AI (2)](https://blog.operasolutions.com/topic/transformative-ai) - [CinemaAI (1)](https://blog.operasolutions.com/topic/cinemaai) - [Data Management (1)](https://blog.operasolutions.com/topic/data-management) - [Data Preparation (1)](https://blog.operasolutions.com/topic/data-preparation) - [Data Quality (1)](https://blog.operasolutions.com/topic/data-quality) - [EMR (1)](https://blog.operasolutions.com/topic/emr) - [Integration (1)](https://blog.operasolutions.com/topic/integration) - [MDM (1)](https://blog.operasolutions.com/topic/mdm) - [Optimization (1)](https://blog.operasolutions.com/topic/optimization) - [Payment Integrity (1)](https://blog.operasolutions.com/topic/payment-integrity) - [Personalization (1)](https://blog.operasolutions.com/topic/personalization) - [Revenue Commander (1)](https://blog.operasolutions.com/topic/revenue-commander) - [Revenue Cycle AI (1)](https://blog.operasolutions.com/topic/revenue-cycle-ai) - [SignalExpressionSyntax (1)](https://blog.operasolutions.com/topic/signalexpressionsyntax) - [Telecommunications and Media (1)](https://blog.operasolutions.com/topic/telecommunications-and-media) - [TravelAI (1)](https://blog.operasolutions.com/topic/travelai) - [predictive analytics (1)](https://blog.operasolutions.com/topic/predictive-analytics) - [revenue cycle management (1)](https://blog.operasolutions.com/topic/revenue-cycle-management) see all [![Opera Solutions](https://www.operasolutions.com/themes/opera/logo.svg)](http://operasolutions.com/) © Opera Solutions OpCo, LLC. 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