About Tirthajyoti Sarkar

Dr. Tirthajyoti Sarkar is a Data Science/ML Manager at Adapdix Corp. He contributes regularly to publications such as KDnuggets and TDS on diverse topics related to data science and machine learning. He has authored data science books and contributes to open source software. Tirthajyoti holds a Ph.D. in EE and is working on an M.S. degree in Computational Data Analytics. Email him at tirthajyoti at gmail[dot]com.

Tirthajyoti Sarkar Posts (32)

• GPU-Powered Data Science (NOT Deep Learning) with RAPIDS - 02 Aug 2021
  
  How to utilize the power of your GPU for regular data science and machine learning even if you do not do a lot of deep learning work.
• Why and how should you learn “Productive Data Science”? - 26 Jul 2021
  
  What is Productive Data Science and what are some of its components?
• How Much Memory is your Machine Learning Code Consuming? - 19 Jul 2021
  
  Learn how to quickly check the memory footprint of your machine learning function/module with one line of command. Generate a nice report too.
• How Can You Distinguish Yourself from Hundreds of Other Data Science Candidates? - 13 Jul 2021
  
  A few easy (and not-so-easy) ways to prove to employers that your skills and attitudes place you in a higher bracket.
• Monte Carlo integration in Python - 24 Dec 2020
  
  A famous Casino-inspired trick for data science, statistics, and all of science. How to do it in Python?
• Fast and Intuitive Statistical Modeling with Pomegranate - 21 Dec 2020
  
  Pomegranate is a delicious fruit. It can also be a super useful Python library for statistical analysis. We will show how in this article.
• How to Create Custom Real-time Plots in Deep Learning - 14 Dec 2020
  
  How to generate real-time visualizations of custom metrics while training a deep learning model using Keras callbacks.
• Pull and Analyze Financial Data Using a Simple Python Package - 09 Jul 2020
  
  We demonstrate a simple Python script/package to help you pull financial data (all the important metrics and ratios that you can think of) and plot them.
• Speed up your Numpy and Pandas with NumExpr Package - 01 Jul 2020
  
  We show how to significantly speed up your mathematical calculations in Numpy and Pandas using a small library.
• Complex logic at breakneck speed: Try Julia for data science - 20 May 2020
  
  We show a comparative performance benchmarking of Julia with an equivalent Python code to show why Julia is great for data science and machine learning.