Collaborating Authors

Educational Setting

Transfer Learning : the time savior


The whole backdrop of Artificial intelligence and deep learning is to imitate the human brain, and one of the most notable feature of our brain is it's inherent ability to transfer knowledge across tasks. Which in simple terms means using what you have learnt in kindergarten, adding 2 numbers, to solving matrix addition in high school mathematics. The field of machine learning also makes use of such a concept where a well trained model trained with lots and lots of data can add to the accuracy of our model. Here is my code for the transfer learning project I have implemented. I have made use of open cv to capture real time images of the face and use them as training and test datasets.

'We need to gather as much data as we can': How AI could change everything about education


The coronavirus lockdown and the school closures that have resulted have had a huge impact on the education of 1.2 billion children across 186 countries. Teachers have been scrambling to keep in touch with their classes, while parents have been trying to keep bored children engaged in learning while cut off from school and fellow students. As a result, virtual classrooms, language apps, online tutoring, and online education software (and new hardware) have seen a surge popularity, with some reports suggesting the market could hit $350 billion by 2025. But can the digital revolution in education, long been promised but rarely achieved, take a step forward as a result of these changes? Speaking at the CogX 2020 conference, Rose Luckin, professor of Learner Centered Design at University College London's Knowledge Lab, argued that the only way for the industry to evolve was to build on what it has learnt recently.

What is the Future of Artificial Intelligence in K-12 Education?


Among the other questions being asked as a result of the current pandemic is, "What will the rise of artificial intelligence mean for K-12 education?" It would seem safe to assume that the rush to online learning and the adoption of new technologies will inevitably lead educators to embrace tools powered by artificial intelligence. But according to Robert F. Murphy, that more optimistic vision for AI will probably be tempered for now by budget shortfalls that "may seriously delay" school districts from making those types of investments anytime soon. Murphy is an independent education consultant with over two decades of research experience, including as a senior policy researcher for the international think tank RAND Corporation and as the director for evaluation research at SRI International, a scientific research center. In a paper authored last year for RAND, Murphy addressed the more fundamental issues of AI that need to be considered, regarding its further adoption.

Getting Girls Into the Artificial Intelligence Pipeline


The term artificial intelligence (AI) was coined 64 years ago at a scholarly conference. The AI field hasn't remained the theoretical province of computer scientists and mathematicians; it now is a pervasive part of everyday life. With a technology this powerful, it is critical to include the perspectives of all women, including those from underrepresented communities. AI applications -- based on algorithms -- are found in robotics, machine learning, natural language processing, machine vision, speech recognition and more. These applications are found in homes, vehicles and myriad other aspects of daily life.

Deep Learning Prerequisites: The Numpy Stack in Python (V2+)


Deep Learning Prerequisites: The Numpy Stack in Python (V2+), Preview this course The Numpy, Scipy, Pandas, and Matplotlib stack: prep for deep learning, machine learning, and artificial intelligence BESTSELLER Created by Lazy Programmer Inc.  English [Auto-generated] Free Coupon Dicount Online Courses Udemy

Introduction to AI, Machine Learning and Python basics


Free Coupon Discount Preview this course Introduction to AI, Machine Learning and Python basics, Learn to understand Artificial Intelligence and Machine Learning algorithms, and learn the basics of Python Programming

The State of AI - MIT Technology Review


Dr. Andrew Ng is a globally recognized leader in artificial intelligence. He was until recently chief scientist at Baidu, where he led the company's approximately 1,300-person AI group and was responsible for driving its global AI strategy and infrastructure. He was also the founding lead of the Google Brain team. In addition, Dr. Ng is co-chairman and cofounder of Coursera, the world's leading MOOC (massive open online course) platform, and an adjunct professor of computer science at Stanford University. He has authored or coauthored over 100 research papers in machine learning, robotics, and related fields.

A child of the slums


I scrambled up a ladder to the tin roof of our house, clutching a book about the evolution of animals. I was 10 years old, and I'd just finished cooking dinner for my entire family—a task that was my daily responsibility. From my perch, I could look out at the slum where we lived in a small town in India. But that wasn't what drew me to the roof: We didn't have any lamps in our house, so I needed sunlight to read my book. I didn't know it at the time, but that study routine was my ticket to a career as a scientist. > “I hope others can take inspiration from my story and realize … they, too, can persevere.” My father—a laborer—didn't let me attend school initially. I was always jealous of my younger brother when he set off to school each day. So, one day, when I was 5 years old, I followed him and hid under the teacher's desk. She noticed me and sent me home. But the next day, she called my father and told him that he should put me in school. Much to my delight, my father said yes. I had a passion for learning, and—despite the hunger pangs I went to school with most days—I quickly shot to the top of my class. When I was 10 years old, my father sent me to a better school outside our neighborhood, one that was mostly attended by students from wealthier families. I was at the top of the class there, too. But I was treated poorly by classmates who saw me as a child of the slums. I also suffered from embarrassment during biology labs because I was very short—due to malnutrition, I suspect—and I had to stand on a chair to see into the microscope. When I graduated from high school, I wanted to become an engineer. My father was eager for me to attend university, but he told me I couldn't study engineering because it was for boys; he said I should study food science instead. My initial reaction was that food science was the last thing I wanted to study. After a childhood preparing meals for my family, there was nothing I hated more than cooking. I enrolled in a food science program anyway, and I quickly discovered that food science wasn't so bad after all. It was a real science—something akin to chemistry—that involved hypothesis testing and experimentation. Soon enough, I was hooked. While attending university, I lived in a hostel near campus, paying my tuition and living expenses with the help of student loans my father secured for me as well as my side job as a research assistant. My room had a lamp, and I was thankful every night that I had light to study under—something I have learned to never take for granted. In the years that followed, I received a Ph.D. in food engineering and was appointed to a faculty position—milestones that felt far removed from my beginnings in the slums. But shortly thereafter, I began a collaboration that brought me back to my roots. I worked with a company that wanted to tackle malnutrition in India's slums. When representatives from the company first approached me, they said, “You'd need to go to the slums and talk with people”—thinking that I'd never done that before. “That's no problem,” I replied. “I grew up in the slums.” As part of my work with the company, I modified the ingredients in a traditional Indian flatbread called chapati, which I'd made every day growing up. I realized it was the perfect vehicle to introduce more nutrition into the diet of poor people, because it was a staple eaten at every meal. I experimented with the ingredients and landed on a recipe that replaced wheat flour with cheap, locally grown grains that contain more minerals, protein, and dietary fiber. Other researchers laughed at me when I started to work on chapati because they didn't think there'd be much science, or innovation, associated with it. But I've since proved them wrong. My work has won numerous national and international awards, and companies, nonprofit organizations, and government agencies have all sought my expertise. In my life, I've faced poverty, hunger, and discrimination. But I didn't let them hold me back. I pushed through the obstacles and learned lessons from them that helped propel me forward. I hope others can take inspiration from my story and realize that—despite the challenges they may be facing—they, too, can persevere.