In a previous blog (The difference between statistics and data science), I discussed the significance of statistical inference. In this section, we expand on these ideas
The goal of statistical inference is to make a statement about something that is not observed within a certain level of…Continue
Added by ajit jaokar on March 22, 2020 at 2:22pm — No Comments
Due to COVID19, we already have 1000 deaths in Italy.
Two months ago, these folks, many of them elderly, would have been celebrating Christmas and looking forward to the next Christmas – knowing that northern Italy has one of the best healthcare systems in the world
But apart from the human cost, the…Continue
Added by ajit jaokar on March 14, 2020 at 1:00pm — No Comments
Kubernetes is being described as the next ‘Java’ i.e. it is fast becoming an endemic/ underlying platform for the whole industry just like the Java programming language.
For the first time, we are seeing the entire ecosystem aligning around the single platform via the Cloud native foundation.
Kubernetes is the underlying technology behind a term called ‘Cloud Native’
The Cloud Native foundation defines the term ‘Cloud Native’ as:
Added by ajit jaokar on March 10, 2020 at 11:00am — No Comments
I saw a post recently which claimed that AI can help doctors diagnose coronavirus
On the face of it - this sounds like a positive development but I wonder if it is?
As I understand it, a single Chinese…Continue
This post is based on two insightful threads I read online (References below)
Based on these, I address the question of ‘The difference between Statistics and Data Science’. Traditionally, most people, including me, would say that ‘statistics came first and Data Science builds upon statistics’. This chain of thought is valid but as you see…Continue
Added by ajit jaokar on February 23, 2020 at 11:49am — No Comments
Which masters or PhD course should I choose for Data Science or Artificial Intelligence?
This is one of the most common questions I am asked
Here is my view – and the usual caveats apply – i.e. the viewpoint is personal and is not associated with any company or institution I am…Continue
Added by ajit jaokar on February 17, 2020 at 7:12am — No Comments
In this post, we explore two terms which are becoming relatively common in professional machine learning applications – MLOps and DevOps
The term MLOps refers to a set of techniques and practises for data scientists to collaborate operations professionals.. MLOps aims to manage deployment of machine learning and deep learning models in large-scale production environments.
The term DevOps comes from the software…Continue
Added by ajit jaokar on February 12, 2020 at 10:00pm — No Comments
I often use this quote from Isaac Newton in my teaching.
AI is a vast and a complex subject. No matter how much you know - you realise that there is really a vast amount more to learn. So, my way of learning a subject as complex and dynamic as AI, is to share my insights. This helps me to refine my own thinking.
I also follow…Continue
Added by ajit jaokar on January 26, 2020 at 12:30pm — No Comments
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…Continue
Added by ajit jaokar on January 20, 2020 at 1:06pm — No Comments
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…Continue
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…Continue
Added by ajit jaokar on December 29, 2019 at 11:30pm — No Comments
You can always learn a lot from the papers presented at NeurIPS
There is some good analysis already on the web.Continue
Added by ajit jaokar on December 25, 2019 at 7:54am — No Comments
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) ,…Continue
Added by ajit jaokar on December 22, 2019 at 1:30pm — No Comments
Academia and industry take different approaches to building machine learning and deep learning models
Here are seven differences
1) Approach to accuracy:…Continue
Added by ajit jaokar on December 18, 2019 at 12:45pm — No Comments
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 –…Continue
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
Added by ajit jaokar on December 3, 2019 at 12:20pm — No Comments
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…Continue
Added by ajit jaokar on November 24, 2019 at 8:54am — No Comments
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…Continue
Added by ajit jaokar on November 11, 2019 at 11:00am — No Comments
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…Continue
Added by ajit jaokar on October 27, 2019 at 10:30am — No Comments
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…Continue