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Gradient as a Guide : A Simple Game   The Backpropagation algorithm is the powerhouse of all Deep Learning models. It is one of the methods of efficiently calculating Gradient for billions of parameters. Therefore, it is vital to understand how the Gradient information g...

Jupyter notebook has always been a de-facto choice when you teach the Python programming language or while developing prototype machine learning models or doing exploratory data analysis. The reasons are manifold. The most important reason is due to its ability to interleave the rich set of explanatory notes using markdown cells and ...

Motivation Are you wondering about the peculiar use of a sinusoidal function to encode the positional information in Transformer architecture? Are you asking why not just use simple one-hot encoding or something similar to encode positions?. Welcome, this article is for you. Perhaps you are here after reading a few articles explaining the posit...

Initially, I thought of writing an article on transformer architecture. However, I realized that it would go beyond some 90 pages if I cover every detail of it. So I thought of putting the presentation (which is almost self-reliant) prepared by me for the deep learning course taught at IITM by Prof.Mitesh Khapra. Here is the presentation (wait ...

I struggle a lot whenever I learn new mathematical concepts and always sought for some sort of visualization to ease the learning process. I hope I am not alone. We are all comfortable at learning something by looking at the pictures from our childhood onwards. Our brain is wired like that. However, as we progress in the various stages of the ed...

3.RandomProcess A Random process could be thought of as a collection of indexed random variables (i.e., a vector) that evolves in time . Each RV (element) in a collection (vector) follows a specific distribution. If all RVs in a collection have the same distribution and are independent of each othe...

layout: page keywords: “Estimation, Jupyter notebook” title: “Linear Estimator for a Random Process” date: 2021-05-25 tags: Probability Mathematics key: “LERP-2105” comment: true — 2.CovarianceAndEstimator Oftentimes, statistical averages such as mean, variance, $n$th order moments, correlation...

1.Random Variables In [1]: import numpy as np from matplotlib import pyplot as plt from matplotlib import transforms as trans from scipy import special plt.style.use('ggplot') In [2]: %matplotlib inline Let us simulate a coing tossing...