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Ajit jaokar's Blog (58)

Can we fix Smart City deployments using AI, Cloud and Video?

Introduction

I spoke at the iot expo on AI and smart cities  in London this week

Smart cities have been around for more than a decade

The overall numbers for Smart cities are promising

  • 2018 over $81 billion was spent on Smart City initiatives and this number is expected…
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Added by ajit jaokar on March 18, 2019 at 12:35am — No Comments

Explaining AI from a Life cycle of data

 

Background

When I was teaching a session on AI at an MBA program at the London School of Economics,   I thought of explaining AI from the perspective of the life-cycle of Data. This explanation is useful because more people are used to data (than to code). I welcome comments on this approach. Essentially, we consider how data is used and transformed for AI and what are its…

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Added by ajit jaokar on March 4, 2019 at 11:05am — No Comments

Python machine learning libraries

Introduction

This blog is a part of the learn machine learning coding basics in a weekend . We recommend the book Python Data Science Handbook by Jake…

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Added by ajit jaokar on February 19, 2019 at 1:30pm — No Comments

Learn #MachineLearning Coding Basics in a weekend - Glossary and Mindmap

For background to this post, please see Learn #MachineLearning Coding Basics in a weekend. Here,we present the glossary that we use for the coding and the mindmap attached to these classes and upcoming book. …

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Added by ajit jaokar on February 11, 2019 at 10:30am — 5 Comments

Learn #MachineLearning Coding Basics in a weekend – a new approach to coding for #AI

image source - wikipedia

UPDATE

Hello all

we are now closing this 

we have been…

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Added by ajit jaokar on January 30, 2019 at 12:00pm — 327 Comments

Advice to a fresh graduate for getting a job in AI/ Data Science

 

After a recent webinar, I was asked about advice for getting a job in AI for a fresh graduate

 

This is a good question and not often answered

Here are my thoughts

 

Background

  • Firstly, AI is a vast topic. Everyone has a limited view on AI based on their personal…
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Added by ajit jaokar on January 21, 2019 at 2:22pm — No Comments

The Mathematics of Data Science: Understanding the foundations of Deep Learning through Linear Regression

 

Note: This is a long post, but I kept it as a single post to maintain continuity of the thought flow

In this longish post, I have tried to explain Deep Learning starting from familiar ideas like machine learning. This approach forms a part of my forthcoming book. You can connect with me on Linkedin to know more about the book. I have used this approach in my teaching. It is based on ‘learning by…

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Added by ajit jaokar on January 14, 2019 at 12:29pm — 2 Comments

AI / Machine learning Cloud APIs: AWS – Azure - GCP - our experience

Most of us start working with specific programming languages like TensorFlow and Pyspark

So, we are relatively not so used to working with Cloud APIs.

But Cloud APIs for Machine Learning and Deep Learning can make your life a lot easier in building AI and Machine Learning services

Of course, the Cloud APIs have a cost – but they…

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Added by ajit jaokar on January 5, 2019 at 2:00pm — 1 Comment

Why I agree with Geoff Hinton: I believe that Explainable AI is over-hyped by media

 

Geoffrey Hinton dismissed the need for explainable AI. A range of experts have explained why he is wrong.

 

I actually tend to agree with…

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Added by ajit jaokar on December 27, 2018 at 12:30pm — 2 Comments

A simplified explanation for Understanding the Mathematics of Deep Learning

Introduction

In this post, I explain the maths of Deep Learning in a simplified manner.  To keep the explanation simple, we cover the workings of the MLP mode (Multilayer Perceptron). I have drawn upon a number of references – which are indicated in the post in the relevant sections.

 

Deep Learning models are playing a significant role in many domains. In the simplest case, deep learning involves stacking multiple neural network layers to address a…

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Added by ajit jaokar on December 17, 2018 at 11:10am — No Comments

Interpreting Exploratory Data Analysis (EDA)

Introduction

Exploratory Data Analysis (EDA) is an approach/philosophy for data analysis that employs a variety of techniques (graphical and quantitative) to better understand data. It is easy to get lost in the visualizations of EDA and to also lose track of the purpose of EDA. EDA aims to make the downstream analysis easier.…

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Added by ajit jaokar on December 6, 2018 at 5:49am — No Comments

The Halley’s comet Data Scientist

Image source: Wikipedia

Introduction

This post is about how not to be the Halley’s comet Data Scientist i.e. to keep yourselves motivated in your Data Science journey

The views expressed here are my own

Many professionals want to transition their career to AI.

But most will not

Often, we see a…

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Added by ajit jaokar on November 15, 2018 at 12:49pm — 2 Comments

AI technologies used in Robotics

 

 

Background

 

Robotics today is not the same as assembly line Robots of the industrial age because AI is impacting many areas of Robotics.

Specifically, AI is changing Robotics in two key areas

  1. Robots are becoming autonomous…
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Added by ajit jaokar on November 7, 2018 at 4:32am — No Comments

How to Choose a Machine Learning Model – Some Guidelines

 

 

In this post, we explore some broad guidelines for selecting machine learning models

 

The overall steps for Machine Learning/Deep Learning are:

  • Collect…
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Added by ajit jaokar on October 15, 2018 at 11:30am — 7 Comments

AI and Algorithmocracy: What the Future Will Look Like

Introduction

With the recent news about Facebook and Cambridge analytica, we are rightly concerned about the power and impact of algorithms to shape political…

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Added by ajit jaokar on October 1, 2018 at 2:00am — No Comments

MBA vs. Data Science qualifications: Does #AI and #DataScience explain the fall in MBA applications?



Last week, the financial times wrote that there was a sharp fall in MBA applications in the USA.

The Elite MBA programs were not affected by this trend, but most others were 

Many factors contribute to this fall in…

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Added by ajit jaokar on September 24, 2018 at 11:20am — No Comments

Landing a 150k USD #datascientist job: Seven things you need to know

 

On Linkedin, many Data Science enthusiasts who aspire to be Data Scientists follow me.

 

One person asked the question:

 

What do I need to know to get a $150K job as a Data Scientist?

 

It’s a good…

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Added by ajit jaokar on September 16, 2018 at 12:28am — 1 Comment

How to use IoT datasets in #AI applications (full stack)

Introduction

Recently, google launched a Dataset search – which is a great resource to find Datasets.  In this post, I list some IoT datasets which can be used for Machine Learning or Deep Learning applications. But finding datasets is only part of the story.  A static dataset for IoT is not enough i.e. some of the interesting analysis is in streaming mode. To…

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Added by ajit jaokar on September 12, 2018 at 3:00am — No Comments

How to create an #Enterprise #AI Business case driven by Data

Introduction

In a previous post (four quadrants of the Enterprise AI business case) – I laid the foundations of a strategy for deploying Enterprise AI. In this post, we…

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Added by ajit jaokar on September 2, 2018 at 4:53am — No Comments

Can we use deliberate practise for learning to code #AI and #machinelearning

In this post, I explore if ideas of deliberate practise can be applied to teaching coding for Artificial Intelligence / Machine Learning

I am exploring these ideas in a free coding workshop/ meetups in London.

There…

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Added by ajit jaokar on August 18, 2018 at 10:30pm — 7 Comments

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