This is a great interview with Abhik Banerjee. Abhik is a Staff Data Scientist at Kohl's Technology (at the Kohl's departmental stores) where he leads a team on machine learning and data mining projects. He also provides strategic direction around these areas to senior executives at Kohl's. Abhik has an interesting role because he has to marry online and physical store analytics to provide insights to Kohl's. Abhik received his MS in computer science from the University of Cincinnati in 2012. Welcome to another episode of Flyover Labs. Today we are lucky enough to have Abhik Banerjee with us. And Abhik is a Staff Data Scientist at Kohl's Department Stores where he works on machine learning and data mining projects.

Health Catalyst has created Healthcare.ai, a website that offers free open source predictive analytics software for hospitals and other healthcare organizations. "Wherever you have a data set that you pull together, you can create a model based on that by using these tools," said Levi Thatcher, director of data science at Health Catalyst. Machine learning and predictive analytics to improve health outcomes has so far been limited to an elite group of data scientists, mostly in the nation's top academic medical centers, he pointed out. Healthcare.ai – open source predictive analytics software – is part of a mission to make machine learning accessible to the thousands of healthcare professionals with only basic technical skills, but who share an interest in using the technology to improve patient care, Thatcher explained. By making its central repository of proven machine learning algorithms freely available, Healthcare.ai opens the doors to a large, diverse group of technical healthcare professionals to quickly use machine learning tools to build accurate models.

For years now, some of the best, wildest, most moving or revealing stories we've been telling ourselves have come not from books, movies or TV, but from video games. So we're starting an occasional series, Reading The Game, in which we take a look at some of these games from a literary perspective. Seeded onto a pinkish and poisoned world of scouring winds, I stumbled from my broken spaceship, unsure of my footing or anything else. I saw strange plants moving, the stalagmite spikes of ore deposits like plutonium fangs, the wreckage of my crash, dust. When I moved, I heard nothing but the crunch of my heavy boots and the occasional chime from my spacesuit -- followed, always, by the weirdly autotuned computer voice in my ear saying, "Environmental protection falling ..." And hers was the only human voice left to speak in the whole of this impossible universe.

Data mining using machine learning enables businesses and organizations to discover fresh insights previously hidden within their data. Whether exploring oil reserves, improving the safety of automobiles, or mapping genomes, machine-learning algorithms are at the heart of these studies. At Intel, we are quickly moving machine learning from an academic pursuit to a driver of innovation an...d competitive advantage for our business. To that end, Intel IT developed a machine-learning tool that helps Intel's sales and marketing organization identify which resellers will best connect with customers in specific vertical industries. The machine-learning algorithm helps us learn more about our resellers by classifying them and then supplementing this information with another algorithm that mines resellers' website content.

Editor's Note: Malika Cantor is a partner at Comet Labs, a venture capital firm and research lab focused on artificial intelligence, and Micki Seibel is head of product at Orange Silicon Valley, part of French telecommunications giant Orange. The two organizations recently partnered on the publication of a report entitled: Bringing Digital Intelligence to Indoor Farming -- urban agriculture in the age of AI. Here Cantor and Seibel write about some of the report's key takeaways and data points. Ability to move production closer to the point of consumption Opportunity to drop genetic traits focused on outdoors -- pest resistance, drought tolerance, etc. -- in favor of traits for nutrient density and flavor. Higher nutrient density and less food spoilage due to shorter distance traveled Opportunity to broaden the crop portfolio as economies of scale are reached with current crops -(mostly leafy greens, cannabis, and vine crops like tomatoes).

Computational approaches to drug discovery can reduce the time and cost associated with experimental assays and enable the screening of novel chemotypes. Structure-based drug design methods rely on scoring functions to rank and predict binding affinities and poses. The ever-expanding amount of protein-ligand binding and structural data enables the use of deep machine learning techniques for protein-ligand scoring. We describe convolutional neural network (CNN) scoring functions that take as input a comprehensive 3D representation of a protein-ligand interaction. A CNN scoring function automatically learns the key features of protein-ligand interactions that correlate with binding. We train and optimize our CNN scoring functions to discriminate between correct and incorrect binding poses and known binders and non-binders. We find that our CNN scoring function outperforms the AutoDock Vina scoring function when ranking poses both for pose prediction and virtual screening.

Not only will smart cities leverage sensors to use energy efficiently, buildings and highways will also be constructed out of materials that work more intelligently. Taking a nod from natural patterns, material scientists and architects have developed bricks with bacteria, made cement that captures carbon dioxide, and created building cooling systems using nothing but wind and sun. This trend could be a massive opportunity for cities, as well as industries like hospitality that depend on large energy-intensive buildings. MGM Resorts, Wynn, and Las Vegas Sands have all recently been outfitted for solar, for example, showing that large companies are taking the first steps toward sustainable infrastructure, both to cut costs and to appeal to environmentally conscious customers. With a growing need for global initiatives to reduce greenhouse gas emissions, fight climate change, and evolve cruelty-free foods, the race is on to define how we consume protein, potentially without involving any animals.

Uber Acquires Tiny Mysterious Startup To Boost AI-Machine Learning; Will Self-Driving Or Flying ... Machine learning answers'holy grail' questions to accelerate drug development BenevolentBio's artificial intelligence could discover a better treatment for ALS 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.

Think Python: How to Think Like a Computer Scientist Allen Downey, 2012 Automate the Boring Stuff with Python: Practical Programming for Total Beginners [Buy on Amazon] Al Sweigart, 2015 Learn Python the Hard Way [Buy on Amazon] Zed A. Shaw, 2013

In this week's column Kehlan looks at the growing influence of artificial intelligence and robotics in the workplace and how nearly half of all human jobs could be obsolete within the next few decades. During the American presidential election we saw Donald Trump and Hillary Clinton both work hard on getting votes within the'rust belt' area of America. Steel mill towns and coal districts with jobs that went somewhere else or just went altogether. What wasn't a significant talking point, and was missed by many commentators, was those jobs that are gone forever. Humans are being replaced by robotics and that will only increase in the next number of decades.