Many researchers have studied student academic performance in supervised and unsupervised learning using numerous data mining techniques. Neural networks often need a greater collection of observations to achieve enough predictive ability. Due to the increase in the rate of poor graduates, it is necessary to design a system that helps to reduce this menace as well as reduce the incidence of students having to repeat due to poor performance or having to drop out of school altogether in the middle of the pursuit of their career. It is therefore necessary to study each one as well as their advantages and disadvantages, so as to determine which is more efficient in and in what case one should be preferred over the other. The study aims to develop a system to predict student performance with Artificial Neutral Network using the student demographic traits so as to assist the university in selecting candidates (students) with a high prediction of success for admission using previous academic records of students granted admissions which will eventually lead to quality graduates of the institution. The model was developed based on certain selected variables as the input. It achieved an accuracy of over 92.3 percent, showing Artificial Neural Network potential effectiveness as a predictive tool and a selection criterion for candidates seeking admission to a university.

The Pulitzer Prize-winning book Gödel, Escher, Bach inspired legions of computer scientists in 1979, but few were as inspired as Melanie Mitchell. After reading the 777-page tome, Mitchell, a high school math teacher in New York, decided she "needed to be" in artificial intelligence. She soon tracked down the book's author, AI researcher Douglas Hofstadter, and talked him into giving her an internship. She had only taken a handful of computer science courses at the time, but he seemed impressed with her chutzpah and unconcerned about her academic credentials. Mitchell prepared a "last-minute" graduate school application and joined Hofstadter's new lab at the University of Michigan in Ann Arbor.

Robotics is one of the fast-growing areas of technology that is opening doors to a wide range of industries such as security, automation, healthcare, consumer products, customized manufacturing, and interactive entertainment. According to the latest research of the U.S. The Bureau of Labor Statistics, Robotics Engineering is expected to grow 4% by 2028. The area of Robotics is likely to be in demand due to the emergence of new technologies. Since the future is of robots the demand and interest among robotics enthusiasts is also growing day by day. Here are the top online masters in robotics programs for robotic lovers.

Modern AI Masterclass: Build 6 Real World AI Applications, Harness the power of AI to solve practical, real-world problems in Finance, Tech, Art and Healthcare Created by Dr. Ryan Ahmed, Ph.D., MBA, Kirill Eremenko, Hadelin de Ponteves, SuperDataScience Team,Mitchell Bouchard PREVIEW THIS COURSE - GET COUPON CODE Description Artificial Intelligence (AI) revolution is here! "Artificial Intelligence market worldwide is projected to grow by US$284.6 Billion driven by a compounded growth of 43. Deep Learning, one of the segments analyzed and sized in this study, displays the potential to grow at over 42. AI is the science that empowers computers to mimic human intelligence such as decision making, reasoning, text processing, and visual perception. AI is a broader general field that entails several sub-fields such as machine learning, robotics, and computer vision.

Vector valued functions are often encountered in machine learning, computer graphics and computer vision algorithms. They are particularly useful for defining the parametric equations of space curves. It is important to gain a basic understanding of vector valued functions to grasp more complex concepts. In this tutorial, you will discover what vector valued functions are, how to define them and some examples. A gentle iIntroduction to vector valued functions.

As we all know, Covid-19 struck Wuhan on New Year's Eve in 2019, and the city embraced total lockdown. Soon, the rest of China and the world followed. But what many don't know is Chinese education never went into lockdown. Within less than three months, Beijing Normal University (BNU) started a new semester offering more than 3,000 online courses. BNU could do so only because of China's comprehensive education technology (EdTech) drive in the preceding years, as a blog post at the Oxford Internet Institute elaborates.

In this course you will learn about a Humanoid Robot Animation like walking, talking etc. This is more like a fun kind of course where no hard or complex robotics concept will be taught rather, we will use a software to create a humanoid robot animation. Software use for this course is Choregraphe. This software is actually developed for Real NAO Robot (humanoid Robot). It is a visual programming language. It allows you to: create animations and behaviors for your NAO, test them on a simulated robot before trying them with your real NAO, and also monitor and control NAO.

Levi Belnap wants to make this clear from the beginning--artificial intelligence will never replace human teachers, at least not in our lifetime. What he and his colleagues at Merlyn Mind believe is that AI can enhance teachers' work. On this episode of EdTech Today, Levi introduces us to his nascent company's offering and provides some insights on how they believe the classroom experience can be better for all involved. The company launched out of stealth mode last month to unveil the first digital assistant built specifically for education that empowers teachers to more naturally use the technology in their classrooms and simplify their work. The company also announces it has closed $29 million in funding to date, led by Learn Capital.

Learn Advanced AI for Games with Behaviour Trees Create your own Behaviour Tree API in C# and apply it in the Unity Game Engine Hot & New What you'll learn Description Behaviour Trees (BTs) are an A.I. architecture that provide game characters with the ability to select behaviours and carry them out, through a tree-like architecture that defines simple but powerful logic operations. It can be used across a wide range of game genres from first-person shooters to real-time strategies and developing intelligent characters capable of making smart decisions. The codebase is deceptively simple and yet logical, reusable and extremely powerful. The library is written in C# and implemented in Unity 2020, however will easily port to other applications. In this course, Penny demystifies the advanced A.I. technique of BTs used for creating believable and intelligent game characters in games, using her internationally acclaimed teaching style and knowledge from almost 30 years working with games, graphics, and having written two award-winning books on games AI.

We present HelpViz, a tool for generating contextual visual mobile tutorials from text-based instructions that are abundant on the web. HelpViz transforms text instructions to graphical tutorials in batch, by extracting a sequence of actions from each text instruction through an instruction parsing model, and executing the extracted actions on a simulation infrastructure that manages an array of Android emulators. The automatic execution of each instruction produces a set of graphical and structural assets, including images, videos, and metadata such as clicked elements for each step. HelpViz then synthesizes a tutorial by combining parsed text instructions with the generated assets, and contextualizes the tutorial to user interaction by tracking the user's progress and highlighting the next step. Our experiments with HelpViz indicate that our pipeline improved tutorial execution robustness and that participants preferred tutorials generated by HelpViz over text-based instructions. HelpViz promises a cost-effective approach for generating contextual visual tutorials for mobile interaction at scale.