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Professor Manfred Minimair, Data Science, Seton Hall University

As part of its online M.S. in Data Science program, Seton Hall University in South Orange, New Jersey, has announced new courses in Text Mining and Machine Learning.

Seton Hall's master's program in Data Science is the first 100% online program of its kind in New Jersey and one of very few in the nation.

Quickly emerging as a critical field in a variety of industries, data science encompasses activities ranging from collecting raw data and processing and extracting knowledge from that data, to effectively communicating those findings to assist in decision making and implementing solutions. Data scientists have extensive knowledge in the overlapping realms of business needs, domain knowledge, analytics, and software and systems engineering.

"We're in the midst of a pivotal moment in history," said Professor Manfred Minimair, director of Seton Hall's Data Science program. "We've moved from being an agrarian society through to the industrial revolution and now squarely into the age of information," he noted. "The last decade has been witness to a veritable explosion in data informatics. Where once business could only look at dribs and drabs of customer and logistics dataas through a glass darklynow organizations can be easily blinded by the sheer volume of data available at any given moment. Data science gives students the tools necessary to collect and turn those oceans of data into clear and readily actionable information."

These tools will be provided by Seton Hall in new ways this spring, when Text Mining and Machine Learning make their debut.

Text MiningTaught by Professor Nathan Kahl, text mining is the process of extracting high-quality information from text, which is typically done by developing patterns and trends through means such as statistical pattern learning. Professor Nathan Kahl is an Associate Professor in the Department of Mathematics and Computer Science. He has extensive experience in teaching data analytics at Seton Hall University. Some of his recent research lies in the area of network analysis, another important topic which is also taught in the M.S. program.

Professor Kahl notes, "The need for people with these skills in business, industry and government service has never been greater, and our curriculum is specifically designed to prepare our students for these careers." According to EAB (formerly known as the Education Advisory Board), the national growth in demand for data science practitioners over the last two years alone was 252%. According to Glassdoor, the median base salary for these jobs is $108,000.

Machine LearningIn many ways, machine learning represents the next wave in data science. It is the scientific study of algorithms and statistical models that computer systems use to perform a specific task without using explicit instructions, relying on patterns and inference instead. It is seen as a subset of artificial intelligence. The course will be taught by Sophine Clachar, a data engineer with more than 10 years of experience. Her past research has focused on aviation safety and large-scale and complex aviation data repositories at the University of North Dakota. She was also a recipient of the Airport Cooperative Research Program Graduate Research Award, which fostered the development of machine learning algorithms that identify anomalies in aircraft data.

"Machine learning is profoundly changing our society," Professor Clachar remarks. "Software enhanced with artificial intelligence capabilities will benefit humans in many ways, for example, by helping design more efficient treatments for complex diseases and improve flight training to make air travel more secure."

Active Relationships with Google, Facebook, Celgene, Comcast, Chase, B&N and AmazonStudents in the Data Science program, with its strong focus on computer science, statistics and applied mathematics, learn skills in cloud computing technology and Tableau, which allows them to pursue certification in Amazon Web Services and Tableau. The material is continuously updated to deliver the latest skills in artificial intelligence/machine learning for automating data science tasks. Their education is bolstered by real world projects and internships, made possible through the program's active relationships with such leading companies as Google, Facebook, Celgene, Comcast, Chase, Barnes and Noble and Amazon. The program also fosters relationships with businesses and organizations through its advisory board, which includes members from WarnerMedia, Highstep Technologies, Snowflake Computing, Compass and Celgene. As a result, students are immersed in the knowledge and competencies required to become successful data science and analytics professionals.

"Among the members of our Advisory Board are Seton Hall graduates and leaders in the field," said Minimair. "Their expertise at the cutting edge of industry is reflected within our curriculum and coupled with the data science and academic expertise of our professors. That combination will allow our students to flourish in the world of data science and informatics."

Learn more about the M.S. in Data Science at Seton Hall

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Seton Hall Announces New Courses in Text Mining and Machine Learning - Seton Hall University News & Events

The old way was to write clever code that could handle every possible outcome. But what if you dont know exactly what your inputs will look like, or just need a faster route to the final results? The answer is Machine Learning, and we want you to give it a try during the Train All the Things contest!

Its hard to find a more buzz-worthy term than Artificial Intelligence. Right now, where the rubber hits the road in AI is Machine Learning and its never been so easy to get your feet wet in this realm.

From an 8-bit microcontroller to common single-board computers, you can do cool things like object recognition or color classification quite easily. Grab a beefier processor, dedicated ASIC, or lean heavily into the power of the cloud and you can do much more, like facial identification and gesture recognition. But the skys the limit. A big part of this contest is that we want everyone to get inspired by what you manage to pull off.

Wait, wait, come back here. Have we already scared you off? Dont read AI or ML and assume its not for you. Weve included a category for Artificial Intelligence Blinky your first attempt at doing something cool.

Need something simple to get you excited? How about Machine Learning on an ATtiny85 to sort Skittles candy by color? That uses just one color sensor for a quick and easy way to harvest data that forms a training set. But you could also climb up the ladder just a bit and make yourself a camera-based LEGO sorter or using an IMU in a magic wand to detect which spell youre casting. Need more scientific inspiration? Were hoping someday someone will build a training set that classifies microscope shots of micrometeorites. But wed be equally excited with projects that tackle robot locomotion, natural language, and all the other wild ideas you can come up with.

Our guess is you dont really need prizes to get excited about this one most people have been itching for a reason to try out machine learning for quite some time. But we do have $100 Tindie gift certificates for the most interesting entry in each of the four contest categories: ML on the edge, ML on the gateway, AI blinky, and ML in the cloud.

Get started on your entry. The Train All The Things contest is sponsored by Digi-Key and runs until April 7th.

Continue reading here:
New Contest: Train All The Things - Hackaday

An Israeli-based provider of machine learning-based solutions announced its flu complications algorithm has been selected as part of the Israeli healthcare organizations integrated strategy to enhance its vaccination campaign.

This innovative machine-learning (AI) program from Medial EarlySign is designed to facilitate more effective and targeted outreach to people in need of disease protection.

EarlySigns software applies advanced algorithms to ordinary patient data, collected over the course of routine care.

In a press release on January 14, 2020, EarlySign said its algorithm can flag individuals at high risk for developing flu-related complications and is being used as part of a clinical study undertaken by Maccabi Healthcare Services and EarlySign.

Varda Shalev, M.D., MPH, director of KSM Kahn-Sagol-Maccabi Research and Innovation Institute, founded by Maccabi Healthcare Services, said in this press release, Due to the late arrival of influenza vaccines in Israel this year, the time we have to vaccinate patients this flu season especially those at high risk for developing flu-related complications is much shorter than usual.

The influenza identification algorithm uses EMR generated data to identify and stratify unvaccinated individuals at high risk of developing flu-related complications, often requiring hospitalization.

This is good news since many areas in the Northern Hemisphere have reported increasing rates of influenza infections, according to the Global Flu Update #359, published by the World Health Organization (WHO).

On January 20, 2020, the WHO reported seasonal influenza A(H3N2) viruses have accounted for the majority of detections around the Northern Hemisphere this flu season.

Maccabis clinical study using EarlySigns flu complications algorithm supports the Israeli HMOs commitment to investigating and implementing machine learning-based solutions to improve the health of populations.

The program follows EarlySign collaboration with Geisinger Health System in December 2019, to apply advanced artificial intelligence and machine learning algorithms to Medicare claims data to predict and improve patient outcomes.

Approximately 4.3 million hospital readmissions occur each year in the U.S., costing more than $60 billion, with preventable adverse patient events creating additional clinical and financial burdens for both patients and healthcare systems, said David Vawdrey, Geisingers chief data informatics officer, in a related press release.

The AI vendor and Danville, Pennsylvania based healthcare provider intend to develop models that predict unplanned hospital and skilled nursing facility admissions within 30 days of discharge and adverse events such as respiratory failure, postoperative pulmonary embolism or deep vein thrombosis, as well as postoperative sepsis before they occur.

Maccabi Healthcare Services is Israels 2nd-largest HMO, covering approximately 2.3 million patients, operating 5 regional centers, including hundreds of branches and clinics throughout Israel.

Medial EarlySignenables healthcare providers to identify risks for critical threats, leading to potentially life-changing diagnoses for millions of patients every single day.

Machine-learning (AI) program news published by Precision Vaccinations.

Read more:
AI-System Flags the Under-Vaccinated in Israel - PrecisionVaccinations