Find the Best-Matching Distribution for Your Data Effortlessly
How to find the best-matching statistical distributions for your data points — in an automated and easy way. And, then how to extend the utility further.
Create Synthetic Time-series with Anomaly Signatures in Python
A simple and intuitive way to create synthetic (artificial) time-series data with customized anomalies — particularly suited to industrial applications.
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.
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.
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.
Why and how should you learn “Productive Data Science”?
What is Productive Data Science and what are some of its components?
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.
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.
Monte Carlo integration in Python
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
Pomegranate is a delicious fruit. It can also be a super useful Python library for statistical analysis. We will show how in this article.