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Ajit jaokar's Blog (100)

Deploying machine learning models using Agile

In the previous post, ten strategies to implement ai on the cloud and edge, I discussed strategies for end to end deployment for machine learning modules.

 

How this relates to Agile?

 

Deployment of AI comes within the scope the normal SDLC (software development lifecycle)

So, normal Agile techniques like scrum, sprints, backlog…

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Added by ajit jaokar on January 20, 2020 at 1:06pm — No Comments

Ten strategies to implement AI on the Cloud and Edge

Introduction

The deployment of Machine Learning and Deep Learning algorithms on Edge devices is a complex undertaking. In this post, I list the strategies for deploying AI to Edge devices end-to-end i.e. for the full pipeline covering machine learning (building modules) and deployment (devops)

I welcome your comments on additional ideas that could be included. In subsequent posts, I will elaborate these ideas in detail and…

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Added by ajit jaokar on January 16, 2020 at 11:30am — No Comments

Data science cookbook style code reference in Python for beginners

Here is another resource I use for teaching my students at AI for Edge computing course. I like this resource because I like the cookbook style of learning to code. The resource is based on the book Machine…

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Added by ajit jaokar on December 29, 2019 at 11:30pm — No Comments

NeurIPS 2019 – analysis of papers by themes

You can always learn a lot from the papers presented at NeurIPS

There is some good analysis already on the web.

From Chip Huygen – neurips 2019 analysis and from David…

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Added by ajit jaokar on December 25, 2019 at 7:54am — No Comments

AI and the future of work: Will Artificial Intelligence make us all into Polymaths in the future?

 

AI and the future of work is a major topic of discussion

 

Most views on this subject are negative

 

More broadly, the negative impact of technology has been highlighted by Nicholas Carr (the shallows) ,…

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Added by ajit jaokar on December 22, 2019 at 1:30pm — No Comments

Seven differences between academia and industry for building machine learning and deep learning models

 

 

Academia and industry take different approaches to building machine learning and deep learning models

 

Here are seven differences

1) Approach to accuracy:…

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Added by ajit jaokar on December 18, 2019 at 12:45pm — No Comments

Rule of thumb: Which AI / ML algorithms to apply to business problems

 

How to know which AI/ ML algorithm to apply to which business problem?

This is a common question

I found a good reference for it –…

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Added by ajit jaokar on December 13, 2019 at 10:18am — No Comments

Free open access book on Industry 4.0, factory automation and Edge

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 Antonio Cavadini

The book deals with the transformation of the shop floor and the wider supply chain by the deployment of Industrial IoT

 

Some of…

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Added by ajit jaokar on December 3, 2019 at 12:20pm — No Comments

How to implement Digital Transformation in an Enterprise using artificial intelligence?

 

 

Digital transformation is getting some traction now.

There are many definitions of digital transformation.

For example, according to salesforce  digital transformation is  -    Digital transformation is the process of using…

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Added by ajit jaokar on November 24, 2019 at 8:54am — No Comments

Artificial Intelligence on Edge devices: an engineering led approach

Artificial Intelligence – Cloud and Edge implementations takes an engineering-led approach for the deployment of AI to Edge devices within the framework of the cloud.

We often use the word ‘engineering’ in casual conversation. However, in this context, we attach a specific meaning to Engineering. Engineering is the use of scientific principles to design and build machines, structures, and other items, including bridges, tunnels, roads, vehicles, and…

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

Understanding the applications of Probability in Machine Learning

 

This post is part of my forthcoming book The Mathematical Foundations of Data Science. Probability is one of the foundations of machine learning (along with linear algebra and optimization). In this post, we discuss the areas where probability theory could apply in machine learning applications. If you want to know more about…

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Added by ajit jaokar on October 27, 2019 at 10:30am — No Comments

Correlation does not equal causation but How exactly do you determine causation?

 

 

Introduction

 

Co-relation does not equal causation – is a mantra drilled into a Data Scientist from an early age

That’s fine ..

But very few talk of the follow-on question ..

How exactly do you determine causation?

This problem is…

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Added by ajit jaokar on September 30, 2019 at 6:33am — 3 Comments

TensorFlow 1.x vs 2.x. – summary of changes

Overview of changes TensorFlow 1.0 vs TensorFlow 2.0

Earlier this year, Google announced TensorFlow 2.0, it is a major leap from the existing TensorFlow 1.0. The key differences are as follows:

 

Ease of use: Many old libraries (example tf.contrib) were removed, and some consolidated. For example, in TensorFlow1.x the model could be made using Contrib, layers, Keras or estimators, so many options for the same task confused many new users.…

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Added by ajit jaokar on September 25, 2019 at 11:30pm — 2 Comments

Explaining Logistic Regression as Generalized Linear Model (in use as a classifier)

The explanation of Logistic Regression as a Generalized Linear Model and use as a classifier is often confusing.

In this article, I try to explain this idea from first principles. This blog is part of my forthcoming book on the Mathematical foundations of Data Science. If you are interested in knowing more, please follow me on linkedin Ajit Jaokar

We take the following approach:

  • We see first briefly how…
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Added by ajit jaokar on September 20, 2019 at 11:36am — No Comments

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

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