The arguments / discussions between the Bayesian vs frequentist approaches in statistics are long running. I am interested in how these approaches impact machine learning. Often, books on machine learning combine the two approaches, or in some cases, take only one approach. This does not help from a learning…
ContinueAdded by ajit jaokar on February 21, 2021 at 12:18pm — No Comments
At the #universityofoxford I focus a lot on the mathematics aspect of AI
I recommend eight books for the mathematics of AI
Added by ajit jaokar on February 14, 2021 at 1:41pm — No Comments
I was asked this question: “What distributions do we need to use Deep Learning?”
This is a question with a multi-faceted answer.
The direct answer is that algorithms which are traditionally referred to as deep learning (MLP, CNN, LSTM) do not need to know the distribution in advance since they…
ContinueAdded by ajit jaokar on February 7, 2021 at 1:26pm — No Comments
5G is critical to many business applications.
Below is a great free opensource book to get started with 5G.
But first, here are five reasons why you should study 5G
If you want to deploy broadband within the Enterprise – there are two main options: rely on WiFi or work with the public telecom…
ContinueAdded by ajit jaokar on January 31, 2021 at 1:50pm — No Comments
AI is central to the future competitiveness of nations. Here is a summary of the major initiatives from nations who have declared a national AI strategy. I have listed the original source at the end of the blog. I have added some links in the case of each nation which I found interesting
Added by ajit jaokar on January 24, 2021 at 10:30am — No Comments
The title of this blog is accurate
There are indeed some caveats / disadvantages to automated machine learning.
This blog was motivated by a question in my University of Oxford class effectively asking:
Will automated machine learning take over all the data scientists’ tasks?
If you listen to the…
ContinueAdded by ajit jaokar on January 18, 2021 at 3:00am — No Comments
For my own research and teaching, I follow AI papers. Here is a list of papers I find interesting. I analysed 3 lists (links below) as meta-references for lists of good papers
From that list and also my own interests, here is a set of papers I find interesting in 2020
CORE PAPERS
These influence…
ContinueAdded by ajit jaokar on January 4, 2021 at 3:20am — No Comments
There are six broad questions which can be answered in data analysis according to an article called “What is the question?” By Jeffery T. Leek, Roger D. Peng. These questions help to frame our thinking of data science problems. Here, I propose that these questions also provide a unified framework for relating statistics…
ContinueAdded by ajit jaokar on December 27, 2020 at 3:11pm — No Comments
If you want some holiday reading, here is something for you
I think this is extraordinarily generous
Applications of Deep Neural Networks 575 page free book by Jeff Heaton
TOC below download links at the end of the post
Happy holidays :)
0.1 Introduction . . . .…
ContinueAdded by ajit jaokar on December 24, 2020 at 1:31pm — No Comments
In this article, we discuss how 5G technologies could empower the next generation enterprise AI applications.
Carrier grade or Telco grade applications refer to a system or hardware or software component that is extremely reliable and well tested. In practice, this means applications which have high availability, fast recovery, guaranteed quality of service and redundancy.
For Enterprise…
ContinueAdded by ajit jaokar on December 9, 2020 at 11:39pm — No Comments
Applications of Deep Neural Networks is a free 500 + page book by Jeff Heaton
The contents are as below
The download link is at the bottom of the page
Introduction
Python Preliminaries
Added by ajit jaokar on December 7, 2020 at 5:42am — No Comments
Despite all the havoc, 2020 has been a good year for tech and a good year for AI.
We already see the green shoots of recovery at the end of 2020 and 2021 holds much promise for growth and technology
Here…
ContinueAdded by ajit jaokar on December 3, 2020 at 11:00am — No Comments
Much has been said about GPT-3 already.
With its 175 billion parameters and a massive corpus of data on which it is trained – GPT-3 is already enabling some innovative applications
But GPT-3 could help pave the way for a new way of developing AI models
The GPT-3 paper is called…
ContinueAdded by ajit jaokar on November 30, 2020 at 12:00pm — No Comments
Added by ajit jaokar on November 23, 2020 at 12:46pm — 3 Comments
I am reading a very interesting paper called Principles and Practice of Explainable Machine Learning by
Vaishak Belle (University of Edinburgh & Alan Turing Institute) and Ioannis Papantonis (University of Edinburgh) which presents a taxonomy of explainable AI (XAI).
XAI is a complex subject…
ContinueAdded by ajit jaokar on November 6, 2020 at 2:00pm — No Comments
For the last few years, I have read the free state of AI report
Here are the list of insights which I found interesting
The full report and the download link is at the end of this article
AI research is less open than you think: Only 15% of papers publish their…
ContinueAdded by ajit jaokar on October 27, 2020 at 11:04am — No Comments
Nvidia CEO Jensen Huang proposed an idea which the media has labelled ‘Huang’s law’ along the lines of Moore’s law.
Moore’s predicts that the number of transistors in an integrated circuit doubles every two years.
As per Huang’s law, GPU performance will double every two years.
Whether or not you…
ContinueAdded by ajit jaokar on October 24, 2020 at 2:03pm — No Comments
I always seek good resources for my teaching at #universityofoxford and this is a great free book on Cloud native – a topic that is very much in the focus
The book needs a free registration and is provided as a full ebook by d2iq.
D2iq was formerly mesosphere – the commercial arm of mesos – but…
ContinueAdded by ajit jaokar on October 19, 2020 at 1:32pm — No Comments
Free book - Artificial Intelligence: Foundations of Computational Agents
There are many excellent free books on Python – but Artificial Intelligence: Foundations of Computational Agents is about a subject not commonly covered
I found the book useful as a introduction to Reinforcement Learning
As the title…
ContinueAdded by ajit jaokar on October 1, 2020 at 2:00pm — No Comments
This blog continues from GPT3 and AGI: Beyond the Dichotomy – Part One
GPT3 and AGI
Let’s first clarify what AGI should look like
Consider the movie ‘Terminator’
When the…
ContinueAdded by ajit jaokar on September 25, 2020 at 2:00pm — No Comments
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