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Introducing cricpy:A python package to analyze performances of cricketers

October 28, 2018
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Introducing cricpy:A python package to analyze performances of cricketers

Full many a gem of purest ray serene, The dark unfathomed caves of ocean bear; Full many a flower is born to blush unseen, And waste its sweetness on the desert air. Thomas Gray, An Elegy Written In A Country Churchyard Introduction It is finally here! cricpy, the python avatar , of my R package cricketr is now … Continue reading Introducing...

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Big Data-2: Move into the big league:Graduate from R to SparkR

October 9, 2018
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This post is a continuation of my earlier post Big Data-1: Move into the big league:Graduate from Python to Pyspark. While the earlier post discussed parallel constructs in Python and Pyspark, this post elaborates similar and key constructs in R and SparkR. While this post just focuses on the programming part of R and SparkR it … Continue reading Big...

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My book ‘Practical Machine Learning in R and Python: Second edition’ on Amazon

June 1, 2018
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My book ‘Practical Machine Learning in R and Python: Second edition’ on Amazon

The second edition of my book ‘Practical Machine Learning with R and Python – Machine Learning in stereo’ is now available in both paperback ($10.99) and kindle ($7.99/Rs449) versions.  This second edition includes more content,  extensive comments and formatting for better readability. In this book I implement some of the most common, but important Machine … Continue reading My...

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My book “Deep Learning from first principles” now on Amazon

May 17, 2018
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My book “Deep Learning from first principles” now on Amazon

My 4th book(self-published), “Deep Learning from first principles – In vectorized Python, R and Octave” (557 pages), is now available on Amazon in both paperback ($16.99) and kindle ($6.65/Rs449). The book starts with the most primitive 2-layer Neural Network and works  its way to a generic L-layer Deep Learning Network, with all the bells and … Continue reading My...

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Deep Learning from first principles in Python, R and Octave – Part 8

May 5, 2018
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Deep Learning from first principles in Python, R and Octave – Part 8

1. Introduction You don’t understand anything until you learn it more than one way. Marvin Minsky No computer has ever been designed that is ever aware of what it’s doing; but most of the time, we aren’t either. Marvin Minsky A wealth of information creates a poverty of attention. Herbert Simon This post, Deep Learning from … Continue reading Deep...

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Deep Learning from first principles in Python, R and Octave – Part 7

April 29, 2018
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Deep Learning from first principles in Python, R and Octave – Part 7

Artificial Intelligence is the new electricity. – Prof Andrew Ng Most of human and animal learning is unsupervised learning. If intelligence was a cake, unsupervised learning would be the cake, supervised learning would be the icing on the cake, and reinforcement learning would be the cherry on the cake. We know how to make the icing … Continue reading Deep...

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Deep Learning from first principles in Python, R and Octave – Part 6

April 16, 2018
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Deep Learning from first principles in Python, R and Octave – Part 6

“Today you are You, that is truer than true. There is no one alive who is Youer than You.” Dr. Seuss “Explanations exist; they have existed for all time; there is always a well-known solution to every human problem — neat, plausible, and wrong.” H L Mencken Introduction In this 6th instalment of ‘Deep Learning … Continue reading Deep...

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Deep Learning from first principles in Python, R and Octave – Part 5

March 23, 2018
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Deep Learning from first principles in Python, R and Octave – Part 5

Introduction a. A robot may not injure a human being or, through inaction, allow a human being to come to harm. b. A robot must obey orders given it by human beings except where such orders would conflict with the First Law. c. A robot must protect its own existence as long as such protection … Continue reading Deep...

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Deep Learning from first principles in Python, R and Octave – Part 4

February 26, 2018
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Deep Learning from first principles in Python, R and Octave – Part 4

In this 4th post of my series on Deep Learning from first principles in Python, R and Octave – Part 4, I explore the details of creating a multi-class classifier using the Softmax activation unit in a neural network. The earlier posts in this series were 1. Deep Learning from first principles in Python, R … Continue reading Deep...

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Deep Learning from first principles in Python, R and Octave – Part 3

January 30, 2018
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Deep Learning from first principles in Python, R and Octave – Part 3

“Once upon a time, I, Chuang Tzu, dreamt I was a butterfly, fluttering hither and thither, to all intents and purposes a butterfly. I was conscious only of following my fancies as a butterfly, and was unconscious of my individuality as a man. Suddenly, I awoke, and there I lay, myself again. Now I do … Continue reading Deep...

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