About Starcom: As the Human Experience Company, we are a global media agency that believes in the alchemy of people and technology to create experiences people love and actions brands need. We're powered by the strength of our innovative, driven and intelligent people who are deeply passionate about achieving best-in-class results on behalf of our clients –some of the world's leading marketers. We value you and the work you do. We work hard, but also enjoy scores of perks rooted in our legacy of having one of the strongest agency cultures. Our top-notch health insurance plans and paid time off allow you much-needed time to recharge and achieve the work-life balance you need to bring your absolute best self to work.

NBCUniversal owns and operates over 20 different businesses across 30 countries including a valuable portfolio of news and entertainment television networks, a premier motion picture company, significant television production operations, a leading television stations group, world-renowned theme parks and a premium ad-supported streaming service. Here you can be your authentic self. As a company uniquely positioned to educate, entertain and empower through our platforms, Comcast NBCUniversal stands for including everyone. We strive to foster a diverse and inclusive culture where our employees feel supported, embraced and heard. We believe that our workforce should represent the communities we live in, so that together, we can continue to create and deliver content that reflects the current and ever-changing face of the world.

Jojo Moolayil is an Artificial Intelligence, Deep Learning, Machine Learning & amp; Decision Science professional with over 5 years of industrial experience and published author of the book – Smarter Decisions – The Intersection of IoT and Decision Science. He has worked with several industry leaders on high impact and critical data science and machine learning projects across multiple verticals. He is currently associated with Amazon Web Services as a Research Scientist. He was born and raised in Pune, India and graduated from the University of Pune with a major in Information Technology Engineering. He started his career with Mu Sigma Inc., the world's largest pure-play analytics provider and worked with the leaders of many Fortune 50 clients.

It's crazy how difficult it can be for Data Scientists like myself to evaluate ML models using classic performance metrics properly. Even with access to multiple metrics and scoring methods, it is still challenging to understand the right metrics for the problems I -- and likely many others -- am facing. This is exactly why I use Snitch AI for most of my ML model quality evaluation. PS -- I've been an active member of developing Snitch AI for the past 2 years. Machine Learning Model Validation Tool Snitch AI Empower your Data Science team to deliver robust, trustworthy AI.

  Despite all the havoc, 2020 has been a good year for tech and a good year for AI. We already see the green shoots of recovery at the end of 2020 and 2021 ho…

Data Science is an umbrella term that covers areas – Data Analytics, Big Data, Business Analytics, Machine Learning, Artificial Intelligence and Deep Learning. This immense field has changed what businesses look like into data and convert them into usable insights. Advancement in technologies and data science tools have changed the manners by which organizations work and grow. India, being a mother lode of ability, is the top destination for national and global companies searching for qualified Data Science experts. Over recent years, the demand for Data Scientists has developed exponentially.

AI theory and its technology is rarely consulted in attempted resolutions of social problems. Solutions often require that decision-analytic techniques be combined with expert systems. The emerging literature on combined systems is directed at domains where the prediction of human behavior is not required. A foundational shift in AI presuppositions to intelligent agents working in collaboration provides an opportunity to explore efforts to improve the performance of social institutions that depend on accurate prediction of human behavior. Professionals concerned with human outcomes make decisions that are intuitive or analytic or some combination of both.

Though we cannot tell what the future holds for us, we can make predictions based on trends. JT Kostman Ph.D – A global cyber crime pandemic ($6T annually) and an ever-expanding alphabet soup of data privacy/protection legislation will increasingly require Data Scientists to accept dual responsibilities as data fiduciaries. As the volume, velocity, variety, virality, and viciousness of cyber attacks inexorably increases, AI solutions will increasingly become the only way to compensate for the projected shortfall of 1.8 million cyber security professionals otherwise needed to combat increasingly sophisticated and determined adversaries – and keep corporate executives out of court. Cassie Kozurkov – We can expect to see improvements in tools for data science as more user experience designers take an interest in the data scientist as user. Image data will grow in importance as the camera becomes more than a way to capture memories, but evolves towards a more natural way for users to interact with apps.

Artificial intelligence and machine learning (AI/ML) are increasingly transforming the healthcare sector. From spotting malignant tumours to reading CT scans and mammograms, AI/ML-based technology is faster and more accurate than traditional devices - or even the best doctors. But along with the benefits come new risks and regulatory challenges. For more information see the IDTechEx report on Digital Health 2019: Trends, Opportunities and Outlook. In their latest article Algorithms on regulatory lockdown in medicine recently published in Science, Boris Babic, INSEAD Assistant Professor of Decision Sciences; Theodoros Evgeniou, INSEAD Professor of Decision Sciences and Technology Management; Sara Gerke, Research Fellow at Harvard Law School's Petrie-Flom Center for Health Law Policy, Biotechnology, and Bioethics; and I. Glenn Cohen, Professor at Harvard Law School and Faculty Director at the Petrie-Flom Center look at the new challenges facing regulators as they navigate the unfamiliar pathways of AI/ML.

Artificial intelligence and machine learning (AI/ML) are increasingly transforming the healthcare sector. From spotting malignant tumours to reading CT scans and mammograms, AI/ML-based technology is faster and more accurate than traditional devices – or even the best doctors. But along with the benefits come new risks and regulatory challenges. In their latest article Algorithms on regulatory lockdown in medicine recently published in Science, Boris Babic, INSEAD Assistant Professor of Decision Sciences; Theodoros Evgeniou, INSEAD Professor of Decision Sciences and Technology Management; Sara Gerke, Research Fellow at Harvard Law School's Petrie-Flom Center for Health Law Policy, Biotechnology, and Bioethics; and I. Glenn Cohen, Professor at Harvard Law School and Faculty Director at the Petrie-Flom Center look at the new challenges facing regulators as they navigate the unfamiliar pathways of AI/ML. They consider the questions: What new risks do we face as AI/ML devices are developed and implemented?