Tech Blog
Content Creation
I like to create easy-to-understand visualizations (still/animated) for various Machine Learning topics. Below is a list of my content creation projects.
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Technical Articles
In my free time, I like to write on the topics of Machine Learning, Interview Preparation, PhD and life in general. I believe writing about something helps you understand it even better.
34. What is Average Precision in Object Detection & Localization Algorithms and how to calculate it? A step-by-step visual guide to understanding the mean average precision for object detection and localization algorithms. Read Article 
33. What is Machine Learning System Design Interview and How to Prepare for It? A detailed guide on preparing ML system design interview with a template. Read Article 
32. What are Intrinsic and Extrinsic Camera Parameters in Computer Vision? A detailed explanation of intrinsic and extrinsic camera parameters with the help of visualizations Read Article 
31. Machine Learning Resume that got me shortlisted for Meta, Microsoft, NVIDIA, Uber, Samsung, Intel, and Others A list of things to focus on your resume, an example CV, and template. Read Article 
30. The Dos and Don’ts of a Software Engineer Resume to get you shortlisted for interviews more Improve your resume to get noticed and shortlisted by the recruiters more Read Article 
29. Types of Machine Learning Interviews and how to ace them A detailed guideline on different categories of machine learning interviews and how to prepare for them. Read Article 28. How to Prepare for Coding Interviews? A guide of timeline and resources for your coding interview preparation. Read Article 
27. Difference between AutoEncoder (AE) and Variational AutoEncoder (VAE) How can you compress data or even generate data from random values? That is what Autoencoder and Variational Autoencoder are. Read Article 26. Uber Data Scientist Interview Experience From the recruiter's email to the onsite interview, a detailed timeline of the interview process Read Article 25. Six Levels of Autonomy for Self-driving Cars Illustrated guide to different levels of autonomy for a self-driving car. Read Article 24. How to Answer a Coding Interview Question? A step-by-step guide to help you answer a coding question. Read Article 
23. Seven (7) Essential Data Structures for a Coding Interview and associated common questions Important data structures visualized with animations Read Article 
22. A Beginner’s Guide to Regression Analysis in Machine Learning Regression analysis explained with examples, illustrations, animations and cheat sheets. Read Article 21. How to prepare for a behavioral/soft skills interview? A behavioral interview is an important part of the job process. In this article, we will go through what to expect in a behavioral interview and how to prepare for it. Read Article 
20. Visualizing the Beauty of Pi Various still and animated visualizations made from the digits of Pi Read Article 
19. Types of Regularization in Machine Learning In this article, we will go through what regularization is, why do we need it, and what are different types of commonly used regularization in machine learning models. Read Article 
18. What are Ensemble methods in Machine Learning? A visual walk-through of the ensemble methods in machine learning with a cheatsheet Read Article 
17. 5 essential tips and tricks to writing effective research papers using LaTeX LaTeX is the defacto standard in the engineering and science communities when it comes to writing a thesis, report, or research paper, etc. Read Article 
16. Cheat Sheets for Machine Learning Interview Topics A list of detailed cheatsheets on the topic of Machine Learning. Read Article 
15. MaskTheFace — CV based tool to mask face dataset Convert face dataset to masked dataset Read Article 
14. AnalyzeTheChat — Python-based WhatsApp chat analyzer Analyze your WhatsApp chat in the form of interesting graphs Read Article 
13. Maintaining GitHub stats for more than 14 days Python code for maintaining the Github clones and views statistics for more than 14 days. Read Article 
12. What is a Convolutional Neural Network? A visualization of the basic elements of a Convolutional Neural Network Read Article 
11. PEDRA — Programmable Engine for Drone Reinforcement Learning Applications Python platform for Drones in 3D environments Read Article 
10. Using Python to Monitor Social Distancing in a Public Area Social distancing in a public area to better deal with the pandemic Read Article 
09. Making simple games in Python Interactive python code for the game of Tic-Tac-Toe, Dots-and-Boxes, and Snake-and-Apple Read Article 
08. What is Transposed Convolutional Layer? Explained through animated gifs and python code Read Article 07. A walk through imbalanced classes in machine learning through a visual cheat sheet What imbalanced training data is and how to address it through precision, recall, and f1 score. Read Article 
06. Understanding the Bias-Variance Tradeoff and visualizing it with example and python code What bias-variance tradeoff is, where does it stem from, why is it necessary to be taken into account, how does it affect our underlying system, and what can be done to improve our ML model. Read Article 
05. Deep Reinforcement Learning for Drones in 3D realistic environments A complete code to get you started with implementing Deep Reinforcement Learning in a realistically looking environment using Unreal Gaming Engine and Python. Read Article 
04. My 6 Tips for Surviving a PhD How to cope up with PhD stress? Read Article 
03. Setting up Python platform for Machine Learning projects In this tutorial, we went through the pre-requisites for working on ML projects (or any python project for that matter). Read Article 
02. Difference between Local Response Normalization and Batch Normalization A short tutorial on different normalization techniques used in Deep Neural Networks. Read Article 
01. Difference between AlexNet, VGGNet, ResNet, and Inception In this tutorial, I will quickly go through the details of four of the famous CNN architectures and how they differ from each other by explaining their W3H (When, Why, What, and How) Read Article
