As a part of Twitter Data Analysis, So far I have completed Movie review using R& Document Classification using R. Today we will be dealing with discovering topics in Tweets, i.e. to mine the tweets data to discover underlying topics– approach known as Topic Modeling. A statistical approach for discovering "abstracts/topics" from a collection of text documents based on statistics of each word. In simple terms, the process of looking into a large collection of documents, identifying clusters of words and grouping them together based on similarity and identifying patterns in the clusters appearing in multitude. When we apply Topic Modeling to the above statements, we will be able to group statement 1&2 as Topic-1 (later we can identify that the topic is Sport),statement 3 as Topic-2 (topic is Movies), statement 4&5 as Topic-3 (topic isdata Analytics). Topic Modeling can be achieved by using Latent Dirichlet Allocation algorithm.

Can your financial institution's fraud detection system learn, reason and adapt to new and emerging cyberthreats? Can it identify fraudulent behavior within your account simply by analyzing interactions and patterns? In this day and age, people can access their bank accounts anywhere, anytime. We need strong, agile and efficient fraud detection systems to keep financial institutions and their customers safe. Mobile functionality and safety are among customers' top concerns when it comes to online banking -- so IBM Security Trusteer is releasing new cognitive fraud detection and behavioral biometric functionality that accomplishes just that. This enhanced functionality adds even more strength to an already robust security platform without impacting user experience.

Classification Learner lets you perform common supervised learning tasks such as interactively exploring your data, selecting features, specifying validation schemes, training models, and assessing results. You can export classification models to the MATLAB workspace, or generate MATLAB code to integrate models into applications. Choose your country to get translated content where available and see local events and offers. Based on your location, we recommend that you select: .

Real-time machine learning has access to a continuous flow of transactional data, but what it really needs in order to be effective is a continuous flow of labeled transactional data, and accurate labeling introduces latency. During this year, I heard and read a lot about real-time machine learning. People usually provide this appealing business scenario when discussing credit card fraud detection systems. They say that they can continuously update credit card fraud detection model in real-time (See "What is Apache Spark?", "…real-time use cases…" and "Real time machine learning"). It looks fantastic but not realistic to me.

NEC Corporation, one of Japan's biggest IT providers, says it has built an AI that can rapidly search CCTV footage and spot a specific person out of a million or more faces. The application – snappily titled NeoFace Image data mining – can find wanted criminals, missing kids, and so on, all from video surveillance. We're told "when searching video where roughly one million individual instances of facial data appear, the software is capable of conducting searches within approximately 10 seconds." In other words, you can feed 24 hours of CCTV into NeoFace, and it could identify, say, a million faces in the video frames. Then when you need to find a sought-after person, the software will take just seconds to scan the database and locate them.

IBM has acquired XPS, a Watson-based AI chatbot for personal shopping, from software firm Fluid. Expert Personal Shopper (XPS) uses natural language technology to interact with customers while they shop. IBM invested in Fluid in 2014, as part of a $100m fund it established to contribute to Watson-based businesses and applications. 'In addition to retail, we believe, XPS can be leveraged and applied to the digital properties for brands across a variety of industries' – PAUL PAPAS Watson is IBM's signature artificial intelligence (AI) platform and the cornerstone of the company's future in AI-based business processes and services. The XPS solution and several key members of the XPS team will become part of IBM iX (Interactive Experience).

Microsoft unveils Concept Graph: 'It's time AI learned some common sense' Adobe shows glimpse of future at MAX conference, and it's in A.I. Sinequa's Cognitive Search and Analytics Platform Certified for Cloudera Enterprise to Provide ... Stay up-to-date on the topics you care about. We'll send you an email alert whenever a news article matches your alert term. It's free, and you can add new alerts at any time.

Samsung Galaxy S8: Specs of the flagship to feature an AI that may be called'Bixby' Which job is AI going to eat next? Stay up-to-date on the topics you care about. We'll send you an email alert whenever a news article matches your alert term. It's free, and you can add new alerts at any time.

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