AI bias is in the news – and it’s a hard problem to solve
But what about the other way round?
When AI engages with humans – how does AI know what humans really…Continue
Added by ajit jaokar on June 30, 2019 at 9:19am — No Comments
The Catch 22 problem holding back AI application adoption ...
Last week, there was an interesting report in the MIT technology review that Artificial Intelligence can help construction industry to help see…
Added by ajit jaokar on June 24, 2019 at 12:30am — No Comments
Can design sprints work for Artificial Intelligence applications?
Last week, for the first time, I attended a meetup on Design Sprints( The Design Sprint Underground)
I had heard of Design sprints from Google – but I am not an expert. The organiser, Eran, created…Continue
This post is a part of my forthcoming book on Mathematical foundations of Data Science.
In this post, we use the Perceptron algorithm to bridge the gap between high school maths and deep learning. Welcome comments
As part of my role as course director of the Artificial Intelligence: Cloud and Edge Computing at the University of…Continue
Added by ajit jaokar on June 14, 2019 at 12:33pm — No Comments
Currently, Cloudera is in the news for all the wrong reasons(Cloudera stock down 42%)
Since Cloudera now also incorporates Hortonworks – the current issues are just the latest in the Big Data woes. Apparently, the third vendor…Continue
Added by ajit jaokar on June 10, 2019 at 10:30am — No Comments
After testing this idea for the last few months, we have formally launched this concept
The idea of ‘Data Science Coding in a weekend’ originated from meetups we conducted in London
The idea is simple but effective
We choose a complex section of code and try to learn it in detail over…Continue
Added by ajit jaokar on May 29, 2019 at 7:52am — No Comments
Last week, we launched a free book called Classification and Regression in a weekend. The idea of the ‘in a weekend’ series of books is to study one complex section of code in a weekend to master the concept. This week. we plan to launch a book called “An…Continue
Added by ajit jaokar on May 26, 2019 at 10:00am — No Comments
Cross validation is a technique commonly used In Data Science. Most people think that it plays a small part in the data science pipeline, i.e. while training the model. However, it has a broader application in model selection and hyperparameter tuning.
Let us first explore the process of cross validation itself and then see how it applies to different parts of the data science pipeline
Cross-validation is a resampling procedure used to evaluate machine learning models on a…Continue
As a teacher of Data Science (Data Science for Internet of Things course at the University of Oxford), I am always fascinated in cross connection between concepts. I noticed an interesting image on Tess Fernandez slideshare (which I very much recommend you follow) which talked of…Continue
Added by ajit jaokar on May 10, 2019 at 6:13am — No Comments
Understanding the maths behind forward and back propagation is not very easy.
There are some very good – but also very technical explanations.
For example : The Matrix Calculus You Need For Deep Learning Terence Parr and Jeremy Howard is an excellent resource but still too complex for beginners.
I found a much simpler explanation in the ml cheatsheet.
Added by ajit jaokar on April 30, 2019 at 9:00pm — No Comments
Automated machine learning is a fundamental shift to machine learning and data science. Data science as it stands today, is resource-intensive, expensive and challenging. It requires skills which are in high demand. Automated Machine learning may not quite lead to the beach lifestyle for the data…Continue
Added by ajit jaokar on April 26, 2019 at 10:51am — No Comments
At the Data Science for IoT course at the University of Oxford – I have been working on a strategy implementing Artificial Intelligence holistically on the Cloud and Edge. This is a complex approach with many new concepts to learn.…Continue
Added by ajit jaokar on April 23, 2019 at 11:00am — No Comments
In this post, I explain
To provide some context, I posted…Continue
Added by ajit jaokar on April 17, 2019 at 8:06am — No Comments
“The question is not whether intelligent machines can have any emotions, but whether machines can be intelligent without any emotions”.
The ability of AI to recognise emotions is a fascinating subject and has wide-ranging applications across many fields of…Continue
Added by ajit jaokar on April 7, 2019 at 2:00pm — No Comments
One of the hardest problem in AI is not technical
It is social
Specifically, it is the problem of “educating people for living and working in a world dominated by AI”
This blog is based on my talk and notes in panels at the…Continue
AI and patents - trends to watch from the WIPO technology trends report
WIPO Technology Trends report 2019 came as a surprise to me. We in AI are not used to thinking about patents so much because tools / platforms are mostly Open sourced.
Here are the key…Continue
Added by ajit jaokar on March 22, 2019 at 1:05pm — No Comments
I spoke at the iot expo on AI and smart cities in London this week
Smart cities have been around for more than a decade
The overall numbers for Smart cities are promising
When I was teaching a session on AI at an MBA program at the London School of Economics, I thought of explaining AI from the perspective of the life-cycle of Data. This explanation is useful because more people are used to data (than to code). I welcome comments on this approach. Essentially, we consider how data is used and transformed for AI and what are its…Continue
Added by ajit jaokar on March 4, 2019 at 11:05am — No Comments
Added by ajit jaokar on February 19, 2019 at 1:30pm — No Comments
For background to this post, please see Learn #MachineLearning Coding Basics in a weekend. Here,we present the glossary that we use for the coding and the mindmap attached to these classes and upcoming book. …Continue