image source – wikipedia Update Hello all, The first book is posted on data science central here, and the community group is here. Please join the… Read More »Learn #MachineLearning Coding Basics in a weekend – a new approach to coding for #AI
Based in London, Ajit's work spans research, entrepreneurship, and academia relating to artificial intelligence (AI) with Cyber-Physical systems. He is the course director of the course: Artificial Intelligence: Cloud and Edge Implementations at the University of Oxford. He is also a visiting fellow in Engineering Sciences at the University of Oxford. Besides this, he also conducts the University of Oxford courses: Digital Twins, Cybseecurity, and Agtech. Ajit works as a Data Scientist through his company, feynlabs - focusing on building innovative early-stage AI prototypes for complex AI applications. Besides the University of Oxford, Ajit has also conducted AI courses at the London School of Economics (LSE), Universidad Politécnica de Madrid (UPM), and as part of The Future Society at the Harvard Kennedy School of Government.
After a recent webinar, I was asked about advice for getting a job in AI for a fresh graduate This is a good question and… Read More »Advice to a fresh graduate for getting a job in AI/ Data Science
The Mathematics of Data Science: Understanding the foundations of Deep Learning through Linear Regression
Note: This is a long post, but I kept it as a single post to maintain continuity of the thought flow In this longish post,… Read More »The Mathematics of Data Science: Understanding the foundations of Deep Learning through Linear Regression
Geoffrey Hinton dismissed the need for explainable AI. A range of experts have explained why he is wrong. I actually tend to agree with… Read More »Why I agree with Geoff Hinton: I believe that Explainable AI is over-hyped by media
Introduction In this post, I explain the maths of Deep Learning in a simplified manner. To keep the explanation simple, we cover the workings of… Read More »A simplified explanation for Understanding the Mathematics of Deep Learning
Introduction In this post, I discuss the development of the Enterprise AI business case through a framework of four quadrants. According to Gartner: “The mindset… Read More »Four Quadrants of the Enterprise AI business case
In this post, we explore some broad guidelines for selecting machine learning models The overall steps for Machine Learning/Deep Learning are: Collect… Read More »How to Choose a Machine Learning Model – Some Guidelines
Introduction With the recent news about Facebook and Cambridge analytica, we are rightly concerned about the power and impact of algorithms to shape political debate… Read More »AI and Algorithmocracy: What the Future Will Look Like
MBA vs. Data Science qualifications: Does #AI and #DataScience explain the fall in MBA applications?
Last week, the financial times wrote that there was a sharp fall in MBA applications in the USA. The Elite MBA programs were not affected… Read More »MBA vs. Data Science qualifications: Does #AI and #DataScience explain the fall in MBA applications?