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MLDB Blog

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The business world is full of streams of items that need to be filtered or evaluated: parts on an assembly line, resumés in an application pile, emails in a delivery queue, transactions awaiting processing. Machine learning techniques are increasingly being used to make such processes more efficient: image processing to flag bad parts, text analysis to surface good candidates, spam filtering to sort email, fraud detection to lower transaction costs etc. In this article, I show how you can take business factors into account when using machine learning to solve these kinds of problems with binary classifiers. Specifically, I show how the concept of expected utility from the field of economics maps onto the Receiver Operating Characteristic (ROC) space often used by machine learning practitioners to compare and evaluate models for binary classification. I begin with a parable illustrating the dangers of not taking such factors into account. This concrete story is followed by a more formal mathematical look at the use of indifference curves in ROC space to avoid this kind of problem and guide model development. I wrap up with some recommendations for successfully using binary classifiers to solve business problems.


Digital Offers: Grab the complete Machine Learning Bundle for just 40

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Ever wish you could take some of your extra money and double or even triple it on the stock market? Unfortunately, the market is tricky, it can be hard to know what to do, how to read the trends and figure out where the money is to be made. Luckily, you can get started with all you need to know for only a small investment. With this complete Machine Learning bundle for just 40 you can get access to 64 lectures, 11 hours of content and more at anytime you want it. You can set up historical price databases in MySQL using Python, learn Python libraries and even access the source code any time as a continued resource.


Commoditizing Music Machine Learning : Services

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Five years ago, music personalization at Spotify was a tiny team. The team read papers, developed models, wrote data pipelines and built services. Today personalization involves multiple teams in New York, Boston & Stockholm producing datasets, feature engineering and serving up products to users. Features like Discover Weekly and Release Radar are but the tip of a huge personalization iceberg. One thing we have noticed is the overhead of running services.


IBM and MIT partner to advance AI machine vision

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IBM and the Massachusetts Institute Technology (MIT) are teaming up to advance the development of machine vision using insights from the brain and cognitive research. The multi-year partnership will see IBM Research collaborate with MIT's Department of Brain & Cognitive Sciences (BCS) to advance frontiers of artificial intelligence in real-world audio-visual comprehension technologies. The organisations are building a research laboratory for brain-inspired multimedia machine comprehension (BM3C) in Cambridge, Massachusetts. Together they plan to develop cognitive computing systems that mimic the human ability to understand and integrate input from several sources for use in various computer applications in industries like healthcare, education, and entertainment. MIT researchers will work with IBM scientists and engineers, who will offer technology expertise and advances from the IBM Watson platform.


The Future of Machine Learning

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I listened to this podcast on my drive to Michigan last Friday. If you like to think about the future, and where the puck is going, put your headphones on and listen critically. What is revealed is the way machine learning can be used to create biased and unbiased conclusions. It's always been known that if you start with the wrong hypothesis when using statistical analysis, you will reach a bad conclusion. There is a humorous blog, Spurious Correlations, that turns statistics on its head.


iovation to launch machine learning fraud detection solution

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In addition, the solution reduces friction for existing trustworthy customers by eliminating time consuming and step-up challenges. For more information about iovation, please check the profile in the company database.


5 ways artificial intelligence will help accountants

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The new way of thinking about AI is to see it doing time-consuming tasks, freeing up space for accountants to do the serious thinking and to exercise professional judgement on more complex matters. Despite some people's fears, AI's advocates say it can be a job-creator, not a job-killer. For years, there have been fears that Artificial Intelligence (AI) – smart machines that work and react like humans while having self-learning capabilities – will redefine the role of accountants. Now innovative firms are investing in AI so they can be at the forefront of cognitive technologies. What does the evolution from automation and data-analytics software to AI mean for accountants?


Artificial intelligence helps in the discovery of new materials

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With the help of artificial intelligence, chemists from the University of Basel in Switzerland have computed the characteristics of about two million crystals made up of four chemical elements. The researchers were able to identify 90 previously unknown thermodynamically stable crystals that can be regarded as new materials. They report on their findings in the scientific journal Physical Review Letters. Elpasolite is a glassy, transparent, shiny and soft mineral with a cubic crystal structure. First discovered in El Paso County (Colorado, USA), it can also be found in the Rocky Mountains, Virginia and the Apennines (Italy).


rapidfy-chatbots-live-chat-on-demand

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Rapidfy, an on-demand platform that connects customers with service professionals and small and medium enterprises is looking to improve how these professionals interact with customers. The firm announced today (Sept. Rapidfy's Live Chat feature will allow customers to communicate via a service professional's website, Facebook or the Rapidfy platform. The chatbots will use artificial intelligence to help service professionals reach and communicate with customers in an affordable way. Just last week, Facebook announced 30,000 bots would soon be payment-enabled for the 900 million users of its Messenger platform.


Chatbots, Live Chat Go On-Demand PYMNTS.com

#artificialintelligence

Rapidfy, an on-demand platform that connects customers with service professionals and small and medium enterprises is looking to improve how these professionals interact with customers. The firm announced today (Sept. Rapidfy's Live Chat feature will allow customers to communicate via a service professional's website, Facebook or the Rapidfy platform. The chatbots will use artificial intelligence to help service professionals reach and communicate with customers in an affordable way. Just last week, Facebook announced 30,000 bots would soon be payment-enabled for the 900 million users of its Messenger platform.