Tirthajyoti Sarkar
Towards Data Science
Sunnyvale, CA, United States
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Past articles by Tirthajyoti:
“Digital Twin” with Python: A hands-on example
A step-by-step guide to building a digital twin example of an electronic switch (transistor) with Python. → Read More
How to do “Limitless” Math in Python
How to perform arbitrary-precision computation and much more math (and fast too) than what is possible with the built-in math library in Python. → Read More
Teaching AI to Classify Time-series Patterns with Synthetic Data
How to build and train an AI model to identify various common anomaly patterns in time-series data. → Read More
GPU-Powered Data Science (NOT Deep Learning) with RAPIDS
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. → Read More
Why and how should you learn “Productive Data Science”?
What is Productive Data Science and what are some of its components? → Read More
How Much Memory is your Machine Learning Code Consuming?
Learn how to quickly check the memory footprint of your machine learning function/module with one line of command. Generate a nice report too. → Read More
How Can You Distinguish Yourself from Hundreds of Other Data Science Candidates?
A few easy (and not-so-easy) ways to prove to employers that your skills and attitudes place you in a higher bracket. → Read More
Monte Carlo integration in Python
A famous Casino-inspired trick for data science, statistics, and all of science. How to do it in Python? → Read More
Fast and Intuitive Statistical Modeling with Pomegranate
Pomegranate is a delicious fruit. It can also be a super useful Python library for statistical analysis. We will show how in this article. → Read More
How to Create Custom Real-time Plots in Deep Learning
How to generate real-time visualizations of custom metrics while training a deep learning model using Keras callbacks. → Read More
Pull and Analyze Financial Data Using a Simple Python Package
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. → Read More
Speed up your Numpy and Pandas with NumExpr Package
We show how to significantly speed up your mathematical calculations in Numpy and Pandas using a small library. → Read More
Speed up your Numpy and Pandas with NumExpr package
We show how to significantly speed up your mathematical calculations in Numpy and Pandas using a small library. → Read More
Complex logic at breakneck speed: Try Julia for data science
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. → Read More
AI and Machine Learning for Healthcare
Traditional business and technology sectors are not the only fields being impacted by AI. Healthcare is a field that is thought to be highly suitable for the applications of AI tools and techniques. → Read More
False positives/negatives and Bayes rule for COVID-19 testing
Why both false positives and false negatives are bad for the COVID-19 tests. Why Bayes rule is important for these situations. → Read More
Why math is easy for AI but gardening is not: Moravec’s paradox
For Artificial Intelligence (AI) and Machine Learning (ML) systems, it is easy to do high-level reasoning but acquiring decent sensory perception and motor skills is very hard. → Read More
Demystifying hypothesis testing with simple Python examples
Hypothesis testing is the bread and butter of data science. We demo the concept using simple real-life examples using Python. → Read More
A Single Function to Streamline Image Classification with Keras
Introduction Plenty has been written about deep learning frameworks such as Keras and PyTorch, and how powerful yet simple to use they are for constructing and playing with wonderful deep learning models. There are so many tutorials/articles already written about model architecture and optimizers— the concept of convolution, max pooling, optimizers such as ADAM or RMSprop. > What if, all you… → Read More
Object-oriented programming for data scientists: Build your ML estimator
By Tirthajyoti Sarkar, ON Semiconductor. UPDATE: You will always find the latest Python script (with the linear regression class definition and methods) HERE. Use it to build further or experiment. What is the problem? Data scientists often come from a background which is quite far removed from traditional computer science/software engineering — physics, biology, statistics, economics,… → Read More