I found an interesting, free book which is still a work in progress book – The Data Engineering Cookbook

I will be contributing through the author (Andreas Kretz.com) patreon site : (…

ContinueAdded by ajit jaokar on July 17, 2019 at 11:00am — No Comments

This post is a part of my forthcoming book on **Mathematical foundations of Data Science**.

In the previous blog, we saw how you could use basic high school maths to learn about the workings of data science and artificial intelligence

In this post we extend that idea to learn about Gradient descent

We…

ContinueAdded by ajit jaokar on July 14, 2019 at 12:30pm — No Comments

I highly recommend the #StateofAI 2019 report. I have followed this report from By Nathan Benaich and Ian Hogarth

The report is free and you can download it at stateofai 2019

The report is kind of Mary Meeker theme for AI for me i.e. a great reference…

ContinueAdded by ajit jaokar on July 8, 2019 at 9:04am — 1 Comment

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…*

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…

ContinueAdded by ajit jaokar on June 16, 2019 at 11:04am — 1 Comment

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…

ContinueAdded 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…

ContinueAdded 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…

ContinueAdded 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…

ContinueAdded 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…

ContinueAdded by ajit jaokar on May 13, 2019 at 11:00am — 1 Comment

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…

ContinueAdded 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.

The…

ContinueAdded 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…

ContinueAdded 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.…

ContinueAdded by ajit jaokar on April 23, 2019 at 11:00am — No Comments

In this post, I explain

- How you can participate further in the free book series which we are launching based on the early experiences and
- Useful resources we recommend based on our experience for learning coding for Data Science (using Python – tensorflow and keras)

To provide some context, I posted…

ContinueAdded 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”. *

Marvin Minsky

The ability of AI to recognise emotions is a fascinating subject and has wide-ranging applications across many fields of…

ContinueAdded 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…

ContinueAdded by ajit jaokar on March 29, 2019 at 2:16pm — 2 Comments

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…

ContinueAdded 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

- 2018 over $81 billion was spent on Smart City initiatives and this number is expected…

Added by ajit jaokar on March 18, 2019 at 12:35am — 2 Comments

- Free book: The #dataengineering cookbook by Andreas Kretz
- How to learn the maths of Data Science using your high school maths knowledge - Gradient Descent
- State of #AI 2019 Report
- Why is it hard for AI to detect human bias?
- The Catch 22 problem holding back #AI application adoption ...
- Can design sprints work for Artificial Intelligence applications?
- How to learn the maths of Data Science using your high school maths knowledge

- Free book: The #dataengineering cookbook by Andreas Kretz
- How to learn the maths of Data Science using your high school maths knowledge
- Learn #MachineLearning Coding Basics in a weekend – a new approach to coding for #AI
- Data Science for Internet of Things - The Big Picture
- The Mathematics of Data Science: Understanding the foundations of Deep Learning through Linear Regression
- Free Python Data Science coding Book series
- How to learn the maths of Data Science using your high school maths knowledge - Gradient Descent

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