Ajit Jaokar
Data Science Central
United Kingdom
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Past articles by Ajit:
A minimum viable learning framework for self-learning AI (machine learning and deep learning)
AI is a complex subject and hard to learn Often, in the early stages, people make mistake such as a) They try to learn everything b) They do not know in wh… → Read More
Human In The Loop: A Case for Human Augmented Interaction
I read an article recently, which had a memorable statement: “Just about every successful deployment of AI has either one of two expedients: It has a person… → Read More
Companies who had AI and Digital at their core have fared far better in the pandemic
We knew intuitively that companies that have digital technologies and AI at their core have fared better in the pandemic. But now, there appears to be some e… → Read More
Why AI tools Failed to Help With Detecting COVID
Following on from the article last week – Deep learning in biology and medicine – we discuss another sobering trend - according to some recent research share… → Read More
Deep learning in biology and medicine
Background In this post, we examine applications of deep learning to three key biomedical problems: patient classification, fundamental biological processes… → Read More
Understanding Self Supervised Learning
In the last blog, we discussed the opportunities and risks of foundational models. Foundation models are trained on a broad dataset at scale and are adaptabl… → Read More
2021 predictions and trends for AI
Despite all the havoc, 2020 has been a good year for tech and a good year for AI. We already see the green shoots of recovery at the end of 2020 and 2021 ho… → Read More
Free book - Artificial Intelligence: Foundations of Computational Agents
Free book - Artificial Intelligence: Foundations of Computational Agents There are many excellent free books on Python – but Artificial Intelligence: Foundati… → Read More
GPT3 and AGI: Beyond the Dichotomy – Part Two
This blog continues from GPT3 and AGI: Beyond the Dichotomy – Part One GPT3 and AGI Let’s first clarify what AGI should look like Consider the movie ‘Terminat… → Read More
GPT3 and AGI: Beyond the Dichotomy
Background Earlier this week, I spoke at an interesting online event organized by Khaleej times in the UAE (UAE’s longest running daily English newspaper). T… → Read More
What is the connection between AI, Cloud-Native and Edge devices?
I was asked this question: What is the connection between AI, Cloud-Native and Edge devices? On first impressions, it sounds like an amalgamation of ever… → Read More
Which machine learning / deep learning algorithm to use by problem type
I like to approach algorithms from the perspective of problem solving. I created this list from a Mc Kinsey document (link below). It’s a good indicative app… → Read More
How to design a biased algorithm .. insights from the UK
Background Last week, the UK witnessed chaos over exam results (GCSE and A-levels). The fiasco also provided a textbook case on how to build a biased algori… → Read More
It's tempting to think that GP3 will solve all NLP problems but it does not
In my previous blog what is driving the innovation in nlp and gpt3 , I talked about how GPT3 has evolved from the basic transformer architecture. Based on tha… → Read More
Feature engine python package for feature engineering
In this post, we explore a new python package for feature engineering Feature engineering is the process of using domain knowledge of the data to transfor… → Read More
Why do some traditional engineers not trust Data Science?
Introduction I had this conversation some time ago with an Engineer who came from a traditional background. By that I mean, he had been in the same industry (… → Read More
Why we need more Bayesian trained data scientists than frequentist post COVID 19 ..
Earlier this week, I was speaking at an event on AI for Real Estate where I showed an example from a BBC clip which said that “central London is now a ghost… → Read More
How to approach the study of algorithms?
I have been reading a book recently about algorithms in the wider sense (40 algorithms every programmer should know -book and github link below) I spend a… → Read More
23 sources of data bias for #machinelearning and #deeplearning
In the paper A survey on bias and fairness in machine learning.- the authors outline 23 types of bias in data for machinelearning. The source is good – so bel… → Read More
IoT Anomaly detection - algorithms, techniques and open source implementation
Background Anomaly detection for IoT is one of the archetypal applications for IoT. Anomaly detection techniques are also used outside of IoT. In my teaching… → Read More