Rehan Guha Author - ML Researcher To talk about myself is a bit of a challenge for me as I more comfortable while talking about my work and discussing about Philosophy & Science.

[Paper] Fine-tuning human for LLM projects

In this post, I will talk about a method which I have designed to fine tune a human being to lower the expectation from LLM models.

Beaware of the Bias

This post will give examples of what bias I faced throughout different project I was involved.

[Paper] Benchmarking Gradient Based Optimizers’ Sensitivity to Learning Rate

This post perfroms a comparative study between multiple optimizers and how sensitive it behaves w.r.t. learning rate.

Demistifying Timeseries Decomposition

This post will simplify how time series decomposition work. This is not the exact breakdown of the package but it is a simplified version.

[Paper] Grid Searching -Novel way of Searching 2D Array

This post shows the paper which I have written in the year 2016. It is about searching a 2D array effective and fast.

Breakingdown Timestamp

This post shows us most possible ways to breakdown the timestamp and other features.

Blind/Referenceless Image Spatial Quality Evaluator (BRISQUE)

This links to the a package `brisque` developed for python. BRISQUE algorithm only gets the image whose quality you want to measure. This is thus called, No-Reference or Objective-Blind.

Visualizing Curse of Dimensionality

This post will visually help the readers to understand the curse of dimensionality for higher dimensional data.

Rudimentary Sequence Alignment using Coronavirus Genome

Pairwise sequence alignment is a useful tool in many fields of biology. For example, the similarity between sequences can used be in evolutionary analysis to find out what organisms share a common ancestor.

RGB v. HSV for Computer Vision

Computer vision is an interdisciplinary scientific field that deals with how computers can be made to gain high-level understanding from digital images or videos. If we consider Digital images then it can be represented in different color space and models. The most common model us RBG but is many cases it fails to perform well over other models.

Simpson's Paradox to understand the importance of Causal Structure

Here we will take an example of Simpson's Paradox and try to make a decision from the observed data and figure out the use of the role and importance of Causal Structure.

Cellex Rapid test :: Probability for getting Antibodies for SARS-CoV-2

The Cellex qSARS-CoV-2 IgG/IgM Rapid Test is a lateral flow chromatographic immunoassay which can detect antibodies against th SARS-CoV-2 virus. We will answer a quation what is the probability of a person having an antibody when that is is tested positive for COVID.

Overview of Container Loading Problem

Staring guide for Container Loading Problems. It covers the basic theoretical concepts to kickstart with this problem. The blog talks about the problem space, minimization problem, maximization problem and multiple constraints for the problems.

COVID-19 -Analysis & Inference (Journal)

Updated with my experiements & insights about COVID-19/SARS-CoV-2

Domain Adaptation / Sample Selection Bias

Is the trained model with 90% accuracy is not performing as expected in Production Environment?

Handling Overflow condition in calculating p-Norm

An error that occurs when the computer attempts to handle a number that is too large for it. If during execution of Euclidean Distance it arrives at a number outside this range, How will you handle it ?

Review :: Deep Image Prior

Deep Image Prior is a type of convolutional neural network used to enhance a given image with no prior training data other than the image itself.

Statistical Sampling

Sampling is a fundamental aspect of statistics, but unlike the other methods of data collection, sampling involves choosing a method of sampling which further influences the data that you will result with. There are two major categories in sampling: probability and non-probability sampling.