Lead your own data science projects with the 3 Ps
There’s a lot of literature on learning the technical aspect of data science: statistics, machine learning, data munging, big data. This material will serve you wel...
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More data beats better algorithms – By Tyler Schnoebelen
Most academic papers and blogs about machine learning focus on improvements to algorithms and features. At the same time, the widely acknowledged truth is that throwin...
Data is not facts – the impossibility of being unbiased
Best intentions We talk a lot about making decisions based on data but we need to be careful about how hard and fast those decisions are. Our decisions are only as good ...
‘Rogue Algorithms’ and the Dark Side of Big Data
Most of us, unless we’re insurance actuaries or Wall Street quantitative analysts, have only a vague notion of algorithms and how they work. But they actually affect ou...
How to find out if it's correlation or causation
This article was written by Joseph Rickert. We all “know” that correlation does not imply causation, that unmeasured and unknown factors can confound a seem...
Concise Visual Summary of Deep Learning Architectures
This article was written by Fjodor Van Veen. With new neural network architectures popping up every now and then, it’s hard to keep track of them all. Knowing all th...
Beyond the Hype of Big Data
My favorite quote on Big Data is by Dan Ariely who says “Big Data is like teenage sex, everyone talks about it, no one really knows how to do it, everyone thinks ...
Beginner's guide to the history of data science
This article was written by Hannah Augur. Hannah is a writer, editor and nerd based in Berlin. She’s a researcher with knowledge and work in a variety of fields, i...
Every Data Science Interview Boiled Down To Five Basic Questions
This article was posted by Roger Huang. Roger Huang heads up growth and marketing at Springboard. He broke into a career in data by analyzing $700 million worth of sal...
Finding Career Opportunities in AI
Summary: Are there large, sustainable career opportunities in AI and if so where? Do they lie in the current technologies of Deep Learning and Reinforcement Learning ...