educational setting


VA's AI Tech Sprint yields a tool for matching patients with clinical trials, and more - FedScoop

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A group of high school students was one of the top teams to emerge from the recent AI Tech Sprint by the Department of Veterans Affairs, delivering a web application that could help match cancer patients to clinical trials. The three students from Northern Virginia entered their work in a competition that included software companies like Oracle Healthcare and MyCancerDB. Digital consulting company Composite App took the $20,000 first place prize for its solution -- a tool for helping patients stay on track with their care plan -- but the clinical trials team got an honorable mention. The tech sprint was organized by the VA's new AI institute, and it focused on partnering with outside organizations and companies interested in applying artificial intelligence tools and techniques to VA data. The high school team's members -- Shreeja Kikkisetti, Ethan Ocasio and Neeyanth Kopparapu -- met as part of the Northern Virginia-based nonprofit Girls Computing League.



Covalence for December/January 2020: The emerging world of artificial intelligence

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Since the early days of the Internet, there hasn't been a new technology drawing so much buzz and concern as artificial intelligence. This month, with the help of theologian Ted Peters, we take a closer look at what is at stake as he outlines how our view of AI may color our view of God. It is of course a timely discussion as more of our daily activities are intersecting with AI perhaps with or without our knowledge. The use of computer intelligence is growing, as is our reliance on it to make daily activities easier. Peters though rightly looks at the broad implications from transhumanism to our view of what salvation is.


Classify A Rare Event Using 5 Machine Learning Algorithms - KDnuggets

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Supervised Learning is the crown jewel of Machine Learning. A couple years ago, Harvard Business Review released an article with the following title "Data Scientist: The Sexiest Job of the 21st Century." Ever since its release, Data Science or Statistics Departments become widely pursued by college students and, and Data Scientists (Nerds), for the first time, is referred to as being sexy. For some industries, Data Scientists have reshaped the corporation structure and reallocated a lot of decision-makings to the "front-line" workers. Being able to generate useful business insights from data has never been so easy.


Classify A Rare Event Using 5 Machine Learning Algorithms - KDnuggets

#artificialintelligence

Supervised Learning is the crown jewel of Machine Learning. A couple years ago, Harvard Business Review released an article with the following title "Data Scientist: The Sexiest Job of the 21st Century." Ever since its release, Data Science or Statistics Departments become widely pursued by college students and, and Data Scientists (Nerds), for the first time, is referred to as being sexy. For some industries, Data Scientists have reshaped the corporation structure and reallocated a lot of decision-makings to the "front-line" workers. Being able to generate useful business insights from data has never been so easy.


Opinion: Why a Data Scientist is the hottest job in tech right now Venture

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Written for Daily Hive by Steve Astorino, vice president of Development, Cognos, and Planning Analytics at Hybrid Data Management and Director of IBM Canada Labs, the largest software development organization in Canada. He is the co-author of "Artificial Intelligence: Evolution and Revolution" Harvard Business Review once called Data Scientists "the sexiest job of the 21st century." So what exactly is a data scientist, and what makes it such a hot job in today's market? Despite its rise across Canadian and global business sectors, data science is still largely unknown or misunderstood by the public at large. In one sentence, a data scientist understands how to collect, use, and analyze data using a machine learning model to solve real-world problems.


Intro to Machine Learning with TensorFlow Nanodegree Program

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The field of machine learning continues to boast incredible job growth, salaries, and skill sets that can be used in many different industries. Google utilizes this technology in their Cloud product to allow startups to build machine learning models that work on data of any size, while GE utilizes IoT to help detect and prevent anomalies and crashes in their products. These are just a snapshot of the numerous applications of machine learning in the market today that display the potential for an exponential amount of professional expansion. Currently, just in the US alone, there are over 50,000 open roles for machine learning professionals, so now is the time to develop machine learning expertise! In LinkedIn's 2020 Emerging Jobs report, AI Specialist, a role that includes machine learning, deep learning, TensorFlow, and Python as key skills, boasts 74% annual growth.


Chile is a front-runner in Latin America's Artificial Intelligence race

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Chile is making its mark in the world, and specifically in the Latin America, with its focus on technology. But as the the country moves closer to its goal, it sees the need for more coordinated policies. That and the desire to build a more "informed and knowledge-based" society prompted the creation of its own Ministry of Science, Technology, Knowledge and Innovation in 2018. Andres Couve has spent his entire career working on research and development. A biologist with a PhD degree in Cell Biology from the prestigious Mount Sinai School of Medicine in New York, he also holds a post-doctorate in Neuroscience from University College London (UCL).


Top 10 Machine Learning Courses for 2020

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With solid roots in statistics, Machine Learning is getting one of the most intriguing and quick-paced computer science fields to work in. There's an unending supply of enterprises and applications machine learning can be applied to make them increasingly proficient and wise. Chatbots, spam filtering, ad serving, search engines, and fraud detection, are among only a couple of instances of how machine learning models support regular day to day life. Machine Learning is the thing that lets us discover patterns and make mathematical models for things that would sometimes be unthinkable for people to do. Not at all like data science courses, which contain subjects like exploratory data analysis, statistics, communication, and visualization techniques, machine learning courses concentrate on teaching just the machine learning algorithms, how they work numerically, and how to use them in a programming language.


I had no idea how to write code two years ago. Now I'm an AI engineer.

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Two years ago, I graduated college where I studied Economics and Finance. I was all set for a career in finance. Investment Banking and Global Markets -- those were the dream jobs. Months into the job, I picked up some Excel VBA and learnt how to use Tableau, Power BI and UiPath (a Robotics Process Automation software). I realized I was more interested in picking up these tools and learning to code rather than learning about banking products.