Background

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…

At the #universityofoxford I focus a lot on the mathematics aspect of AI

I recommend eight books for the mathematics of AI

1. The Nature Of Statistical Learning Theory By Vladimir Vapnik.
2. Pattern Classification By Richard O Duda
3. Machine Learning: An Algorithmic Perspective, Second…

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…

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  

Private 5g

If you want to deploy broadband within the Enterprise – there are two main options: rely on WiFi or work with the public telecom…

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

United States of…

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…

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…

Introduction

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…

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 . . . .…

In this article, we discuss how 5G technologies could empower the next generation enterprise AI applications.

What does it mean to develop carrier grade 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…

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

• Assignments…

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…

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…

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…

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…

 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…

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…

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…

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…