— Insight —
For many, “raw” data is ground truth and independent from human judgment. This essay in the The New Atlantis explores how that's a seductive myth.
— Sponsored Link —
Data science and analytics positions are taking the job market by storm. A master’s degree or graduate-level certificate from UW-Madison can jump start your data career. We have 13 online, one-year, full-time, or part-time data programs to fit your life and help you succeed, including GIS, Data Analytics and Actuarial Science. Explore more today.
— Tools and Techniques —
Nice collection of common machine learning algorithms implemented in Python. These "homemade" algorithms are built from scratch and are intended to clearly show how the algorithms work.
Julia is a high-performance programming language that's been designed specifically for scientific and numerical computing. There are a lot of advocates for Julia and it's gaining traction in many enterprise settings. This article explores the current state of Julia's strengths and weaknesses and how you should be thinking about Python and R.
There are a lot of good tips here for Airflow users and if you don't use Airflow, skimming through this will give you an idea of some of it's capabilities.
Luis Serrano has a knack for creating educational math videos that are easy to follow. In this first of a 3-part series, he introduces Linear Regression in a way that relies more on visual understanding than math. Upcoming episodes will cover Logistic Regression and SVMs.
Home Assistant is an open-source home automation platform for Python 3. It's able to integrate data from from a large variety of IoT vendors such as Arduino, Sonos, ecobee, Dark Sky, Nest, Amazon, etc. In other words, it's an integrated platform for controlling your home alarm, lights, thermostat, media players, etc. The newly released Data Science Portal makes it easy to get started and work with the data from those devices using tools such as Pandas.
— Data Viz —
Claus O. Wilke's online book, Fundamentals of Data Visualization, gets two well-deserved mentions this week. The book itself is a top resource for 2018 and this recent chapter is a useful deep dive into the challenges and strategies for visualizing uncertainty.