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Ajit jaokar's Blog (86)

IoT - where are the stream analytics use cases?

I have been looking at this problem over a few years now
The IoT industry often speaks of handling both high volumes and high throughputs of data
However, currently, I find that there are not many use cases for IoT streaming analytics which are unique
The 'unique' and 'currently' bits…
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Added by ajit jaokar on September 14, 2019 at 8:45am — No Comments

“Will china dominate AI?” – is the wrong question

Introduction

 

Will china dominate AI?

When I spoke at the UK China business forum last month, I discussed this topic in response to an audience question.

In the current climate of nationalistic fervour, I see the same question asked in many guises.

For…

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Added by ajit jaokar on September 9, 2019 at 11:32am — No Comments

Can an ethical and algorithmically transparent cloud kitchen prevent future Amazon fires?

Can an ethical and algorithmically transparent cloud kitchen prevent future Amazon fires?

 

We often view AI with suspicion – but AI can be used to solve complex problems currently facing society where innovative approaches are needed

 

For many of us, the Amazon fires are disturbing and a…

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Added by ajit jaokar on August 31, 2019 at 5:14am — No Comments

The AI Edge Engineer: Extending the power of CI/CD to Edge devices using containers

The AI Edge Engineer: Extending the power of CI/CD to Edge devices using containers

Background

At the Artificial Intelligence – Cloud and Edge implementations course – I have been exploring the idea of extending CI/CD to Edge devices using containers. In this post, I present these ideas under the framework of the ‘AI Edge…

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Added by ajit jaokar on August 26, 2019 at 12:23pm — No Comments

Three-way data splits (training, test and validation) for model selection and performance estimation

The use of training, validation and test datasets is common but not easily understood. 

 

In this post, I attempt to clarify this concept. The post is part of my forthcoming book on learning Artificial Intelligence, Machine Learning and Deep Learning based on high school maths.  If you want to know more about the book, please follow me on Linkedin Ajit Jaokar

 

Background

Jason…

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Added by ajit jaokar on August 20, 2019 at 1:58pm — No Comments

Free book - Containerize your Apps with Docker and Kubernetes and impact of containers for AI on Edge devices

Background

Containerize your Apps with Docker and Kubernetes is an excellent free book from Gabriel N. Schenker

You can download the whole book by registering…

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Added by ajit jaokar on August 13, 2019 at 11:12am — No Comments

Tensorflow 2.0 coding workshop notebooks

At our meetup Data Science for Internet of Things, Dan Howarth conducted a workshop on tensorflow 2.0
we plan to…
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Added by ajit jaokar on August 4, 2019 at 12:30pm — No Comments

An elegant way to represent forward propagation and back propagation in a neural network

Sometimes, you see a diagram and it gives you an ‘aha ha’ moment

Here is one representing forward propagation and back propagation in a neural network

I saw it on Frederick kratzert’s blog

 

 …

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Added by ajit jaokar on July 27, 2019 at 9:41am — No Comments

The missing link for IoT - the Cloud

 

Introduction

 

IoT (Internet of Things) has not quite taken off yet as envisaged -  Will the cloud overcome the shortcomings of IoT? I believe that the Cloud is the missing link that enables IoT to create a critical mass towards deployment.

 

The vision outlined here is part of my forthcoming book on Data Science…

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Added by ajit jaokar on July 23, 2019 at 1:07pm — 2 Comments

Free book: The #dataengineering cookbook by Andreas Kretz

 

 

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 : (…

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

How to learn the maths of Data Science using your high school maths knowledge - Gradient Descent

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…

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

State of #AI 2019 Report

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…

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

Why is it hard for AI to detect human bias?

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…

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Added by ajit jaokar on June 30, 2019 at 9:19am — No Comments

The Catch 22 problem holding back #AI application adoption  ...

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…

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Added by ajit jaokar on June 24, 2019 at 12:30am — No Comments

Can design sprints work for Artificial Intelligence applications?

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…

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

How to learn the maths of Data Science using your high school maths knowledge

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

 

Background

As part of my role as course director of the Artificial Intelligence: Cloud and Edge Computing at the University of…

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Added by ajit jaokar on June 14, 2019 at 12:33pm — No Comments

Seduced by the Big Data meme: Hadoop vs the Public Cloud

 

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…

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Added by ajit jaokar on June 10, 2019 at 10:30am — No Comments

Data science Coding in a weekend series of books …

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…

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Added by ajit jaokar on May 29, 2019 at 7:52am — No Comments

Azure Machine Learning concepts - an Introduction

Azure Machine Learning concepts - an Introduction

Introduction

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…

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Added by ajit jaokar on May 26, 2019 at 10:00am — No Comments

Understanding Cross Validation across the Data Science pipeline

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…

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

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