By Dominik Haitz – 5 min read
Drew Conway’s visualization of the data science skill set is an often cited classic. Different opinions and the versatility of the role have spawned numerous variations.
XGBoost Algorithm: Long May She Reign!
By Vishal Morde and Venkat Anurag Setty – 7 min read
I still remember the day 1 of my very first job fifteen years ago. I had just finished my graduate studies and joined a global investment bank as an analyst.
Architecting a Machine Learning Pipeline
By Semi Koen – 18 min read
When developing a model, data scientists work in some development environment tailored for Statistics and Machine Learning (Python, R etc) and are able to train and test models all in one ‘sandboxed’ environment while writing relatively little code.
How to Automate Tasks on GitHub With Machine Learning for Fun and Profit
By Hamel Husain – 13 min read
A tutorial on how to build a GitHub App that predicts and applies issue labels using Tensorflow and public datasets.
Key Kubernetes Concepts
By Jeff Hale – 12 min read
Cloud computing, containerization, and container orchestration are the most important trends in DevOps. Whether you’re a data scientist, software developer, or product manager, it’s good to know Docker and Kubernetes basics.
Scalable Log Analytics with Apache Spark – A Comprehensive Case-Study
By Dipanjan (DJ) Sarkar – 18 min read
One of the most popular and effective enterprise case-studies which leverage analytics today is log analytics. Almost every small and big organization today have multiple systems and infrastructure running day in and day out.
Reinforcement Learning for Combinatorial Optimization
By Or Rivlin – 9 min read
Learning strategies to tackle difficult optimization problems using Deep Reinforcement Learning and Graph Neural Networks.
A guide to Face Detection in Python
By Maël Fabien – 14 min read
In this tutorial, we’ll see how to create and launch a face detection algorithm in Python using OpenCV and Dlib. We’ll also add some features to detect eyes and mouth on multiple faces at the same time.
The Secrets of Successful AI Startups. Who’s Making Money in AI? Part II
By Simon Greenman – 20 min read From Silicon Valley to London to Shanghai AI startups are in abundance. But with any gold rush a few chosen will find gold and most others will go home empty.
Ten random useful things in R that you might not know about
By Keith McNulty – 7 min read R is full of useful stuff. Here are a few things that I use a lot which others may not know about.
The Complete Beginner’s Guide to Machine Learning: Multiple Linear Regression in 4 Lines of Code!
By Anne Bonner – 19 min read Conquer the basics of multiple linear regression (and backward elimination!) and use your data to predict the future!