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COUNTLESS 3D— Vectorized 2x Downsampling of Labeled Volume Images Using Python and Numpy

A visualization of a 2x2x2 downsample of a labeled dataset. This is what COUNTLESS 3D does. Previously, I demonstrated a fully vectorized algorithm, COUNTLESS, that downsampled labeled images by finding the mode of 2×2 patches without counting pixel value frequencies. Here, I generalize COUNTLESS to 3D images using a 2x2x2 patch […]

How I generated inspirational quotes with less than 20 lines of python code

“Don’t think of the overwhelming majority of the impossible.”“Grew up your bliss and the world.”“what we would end create, creates the ground and you are the one to warm it”“look and give up in miracles” All the quotes above have been generated by a computer, using a program that consists […]

How to write a production-level code in Data Science?

dreamstime/Scyther5 Ability to write a production-level code is one of the sought-after skills for a data scientist role— either posted explicitly or not. For a software engineer turned data scientist this may not sound like a challenging task as they might have already perfected their skill at developing production level […]

Learning to analyze huge BigQuery datasets using Python on Kaggle

In this last few weeks I’ve learned how to analyze some of BigQuery’s cool public datasets using Python. If you’re not familiar, BigQuery makes it very easy to query Terabytes amounts of data in seconds. In this post, I’m going to share some tips and tricks for analyzing BigQuery data using […]

Anomaly Detection using Rapidminer and Python

I have always felt that anomaly detection could be a very interesting application of machine learning. I can think of several scenarios where such techniques could be used. In this article I shall describe some experiments I carried out with the Credit Card Fraud Detection dataset from Kaggle. The dataset contains […]

Markov Chain Monte Carlo in Python

A Complete Real-World Implementation of Bayesian Inference The past few months, I encountered one term again and again in the data science world: Markov Chain Monte Carlo. In my research lab, in podcasts, in articles, every time I heard the phrase I would nod and think that sounds pretty cool […]

Open Machine Learning Course. Topic 1. Exploratory data analysis with Pandas

With this article, we, OpenDataScience, launch an open Machine Learning course. This is not aimed at developing another comprehensive introductory course on machine learning or data analysis (so this is not a substitute for fundamental education or online/offline courses/specializations and books). The purpose of this series of articles is to […]

Big Data: What is Web Scraping and how to use it

What is web scraping? It is essential for gathering Big Data sets, which are the cornerstone of Big Data analytics, Machine Learning (ML) and tutoring the Artificial Intelligence (AI) algorithms. The hard point is that information is the most valuable commodity in the world (after time, as you cannot buy […]

Python Basics for Data Science

Python Data Types In Python, we have many data types. The most common ones are float (floating point), int (integer), str (string), bool (Boolean), list. Float – Used for real numbers. Int – Used for integers. Str – Used for texts. We can define strings using single quotes’value’, double quotes”value”, or triple […]