Get yourself trained on Advanced Artificial Intelligence with this Online Training Advanced Artificial Intelligence Projects with Python.
Online Training Advanced Artificial Intelligence Projects with Python
Considered the Holy Grail of automation, data analysis, and robotics, Artificial Intelligence has taken the world by storm as a major field of research and development. Python has surfaced as a dominate language in AI/ML programming because of its simplicity and flexibility, in addition to its great support for open source libraries such as spaCy and TensorFlow.This video course is built for those with a basic understanding of artificial intelligence, introducing them to advanced artificial intelligence projects as they go ahead. The first project introduces natural language processing including part-of-speech tagging and named entity extraction. Wikipedia articles are used to demonstrate the extraction of keywords, and the Enron email archive is mined for mentions and relationships of people, places, and organizations. The spaCy library is used. The next project introduces genetic algorithms. The DEAP library is used. A music data set is used in a genetic algorithm that generates a music playlist satisfying multiple criteria such as song similarity and playlist length. The last project introduces reinforcement learning and deep reinforcement learning. The OpenAI Gym platform and Q-learning algorithm are used to build a game-playing AI.About the AuthorJoshua Eckroth is Assistant Professor of Computer Science at Stetson University, where he teaches Big Data Mining and Analytics, Artificial Intelligence (AI), and Software Engineering. Dr. Eckroth joined the Math and Computer Science Department at Stetson University in Fall 2014. He earned his PhD from Ohio State University in the areas of AI and cognitive science, focusing on abductive reasoning and metareasoning. He is an active researcher with numerous refereed publications in the fields of artificial intelligence and computer science education. Dr. Eckroth also serves as Chief Architect at i2k Connect, LLC., whose mission is to revolutionize the ability of companies to find, filter, and analyze data in documents by extracting essential information from data clutter. In addition, Dr. Eckroth is co-editor of AITopics .org, the Internet’s largest collection of information about the research, the people, and the applications of Artificial Intelligence.
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As a society, we spend hundreds of billions of dollars measuring the return on our financial assets. Yet, at the same time, we still haven’t found convincing ways of measuring the return on our investments in developing people.
And I get it: If my bank account pays me 1% a year, I can measure it to the penny. We’ve been collectively trained to expect neat and precise ROI calculations on everything, so when it’s applied to something as seemingly squishy as how effectively people are learning in the workplace, the natural inclination is to throw up our hands and say it can’t be done. But we need to figure this out. In a world where skills beat capital, the winners and losers of the next 30 years will be determined by their ability to attract and develop great talent.
Fortunately, corporate learning & development (L&D), like most business functions, is evolving quickly. We can embrace some level of ambiguity and have rigor when measuring the ROI of learning. It just might look a little different than an M.B.A. would expect to see in an Excel model.