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Yunus Bastan liked ajit jaokar's blog post Artificial Intelligence on Edge devices: an engineering led approach
yesterday
Scott Mongeau liked ajit jaokar's blog post Understanding the applications of Probability in Machine Learning
yesterday
ajit jaokar liked ajit jaokar's blog post Artificial Intelligence on Edge devices: an engineering led approach
Nov 12
ajit jaokar's blog post was featured

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 buildings. The American Engineers' Council for…See More
Nov 11
ajit jaokar's blog post was featured

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 the book, follow me on…See More
Oct 27
Derick Ehiobu and ajit jaokar are now friends
Oct 16
Mahantesh Angadi commented on ajit jaokar's blog post Learn #MachineLearning Coding Basics in a weekend – a new approach to coding for #AI
"Hi, I am interested, could you please provide the link. Regards,"
Oct 12
John L. Ries commented on ajit jaokar's blog post Correlation does not equal causation but How exactly do you determine causation?
"Well stated.  You can try to boost the national economy by encouraging women to wear miniskirts, but it's probably not going to work.  Causation is something that has to be tested directly, and on many fronts, such as economics, this…"
Oct 7
Prasanth liked ajit jaokar's blog post Tensorflow 2.0 coding workshop notebooks
Oct 7
Lance Norskog commented on ajit jaokar's blog post Correlation does not equal causation but How exactly do you determine causation?
"My brilliant insight: under information theory, signal and noise are a package deal. People usually measure correlation and infer causality by matching signals. But, if the noise profile for a dependent signal cannot possibly match the noise profile…"
Oct 6
Cristopher Masserini liked ajit jaokar's blog post Correlation does not equal causation but How exactly do you determine causation?
Oct 2
ajit jaokar liked ajit jaokar's blog post Correlation does not equal causation but How exactly do you determine causation?
Oct 1
ajit jaokar's blog post was featured

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 ageThat’s fine ..But very few talk of the follow-on question ..How exactly do you determine causation?This problem is further compounded because most books and examples are based on standard datasets (ex: Boston, Iris etc) .These examples do not discuss causation…See More
Sep 30
Blaine Bateman commented on ajit jaokar's blog post TensorFlow 1.x vs 2.x. – summary of changes
"Thank you for this. It would be great to have a 1.x 2.x side by side code example. "
Sep 29
Chris Simokat commented on ajit jaokar's blog post TensorFlow 1.x vs 2.x. – summary of changes
"Really enjoyed the write up thank you. I think the direction of TensorFlow 2 looks really promising, but it seems to be taking awhile to get here. TF2 was announced back in March at TensorFlow Dev Summit, but is still currently a release candidate…"
Sep 26
ajit jaokar's blog post was featured

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

Overview of changes TensorFlow 1.0 vs TensorFlow 2.0Earlier 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. TensorFlow 2.0 promotes TensorFlow Keras for model…See More
Sep 26

Profile Information

Short Bio
My research is focused on Data Science for IoT. I teach same at Oxford Uni and UPM in Madrid (@forumoxford + @citysciences). Also launching a course / certification Data Sciences for IoT for industry. Personal research interests - Deep learning algorithms for IoT/future city domains
My Web Site Or LinkedIn Profile
http://www.opengardensblog.futuretext.com/archives/2016/01/data-sci...
Professional Status
Professor
Years of Experience:
20
Your Company:
futuretext
Industry:
IoT, Telecoms, Smart Cities
Your Job Title:
founder
How did you find out about DataScienceCentral?
Twitter
Interests:
Finding a new position, Networking, New venture, Other

Ajit jaokar's Blog

Artificial Intelligence on Edge devices: an engineering led approach

Posted on November 11, 2019 at 11:00am 0 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

Understanding the applications of Probability in Machine Learning

Posted on October 27, 2019 at 10:30am 0 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

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

Posted on September 30, 2019 at 6:33am 2 Comments

 

 

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…

Continue

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

Posted on September 25, 2019 at 11:30pm 2 Comments

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.…

Continue

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