Ajit jaokar's Blog – September 2019 Archive (5)
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 age
That’s fine ..
But very few talk of the follow-on question ..
How exactly do you determine causation?
This problem is…
ContinueAdded by ajit jaokar on September 30, 2019 at 6:33am — 3 Comments
TensorFlow 1.x vs 2.x. – summary of changes
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.…
ContinueAdded by ajit jaokar on September 25, 2019 at 11:30pm — 2 Comments
Explaining Logistic Regression as Generalized Linear Model (in use as a classifier)
The explanation of Logistic Regression as a Generalized Linear Model and use as a classifier is often confusing.
In this article, I try to explain this idea from first principles. This blog is part of my forthcoming book on the Mathematical foundations of Data Science. If you are interested in knowing more, please follow me on linkedin Ajit Jaokar
We take the following approach:
- We see first briefly how…
Added by ajit jaokar on September 20, 2019 at 11:36am — No Comments
IoT - where are the stream analytics use cases?
Added by ajit jaokar on September 14, 2019 at 8:45am — No Comments
“Will china dominate AI?” – is the wrong question
Introduction
Will china dominate AI?
When I spoke at the UK China business forum last month, I discussed this topic in response to an audience question.
In the current climate of nationalistic fervour, I see the same question asked in many guises.
For…
ContinueAdded by ajit jaokar on September 9, 2019 at 11:32am — No Comments
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