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.
The Digital Shopfloor: Industrial Automation in the Industry 4.0 Era looks like a great free open access book by John Soldatos, Oscar Lazaro and Franco… Read More »Free open access book on Industry 4.0, factory automation and Edge
Introduction This blog is a part of the learn machine learning coding basics in a weekend . We recommend the book Python Data Science Handbook… Read More »Python machine learning libraries
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
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
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
Image source: Wikipedia Introduction This post is about how not to be the Halley’s comet Data Scientist i.e. to keep yourselves motivated in your Data… Read More »The Halley’s comet Data Scientist
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
