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Thomas originally posted this article here at http://twiecki.github.io  Hierarchical models are underappreciated. Hierarchies exist in many data sets and modeling them appropriately adds a boat load of statistical power (the common metric of statistical power). I provided an introduction to hierarchical models in a previous blog post: Best Of Both Worlds: Hierarchical... Read more
Random-Walk Bayesian Deep Networks: Dealing with Non-Stationary Data
Thomas originally posted this article here at http://twiecki.github.io  Most problems solved by Deep Learning are stationary. A cat is always a cat. The rules of Go have remained stable for 2,500 years, and will likely stay that way. However, what if the world around you is changing? This is common, for example... Read more
NYC Pre-K Explorer
Shiny Project contributed by Amy Tzu-Yu Chen – Data Science Student in the NYC Data Science Academy Bootcamp Motivation In 2013, Mayor De Blasio campaigned on a promise of universal pre-kindergarten. The program makes access to free pre-kindergarten education available to all NYC families, regardless of child’s abilities and family income. Now, three years... Read more
Teaching pivot / un-pivot
Co-written by John Mount and Nina Zumel Introduction In teaching thinking in terms of coordinatized data we find the hardest operations to teach are joins and pivot. One thing we commented on is that moving data values into columns, or into a “thin” or entity/attribute/value form (often called “un-pivoting”, “stacking”,... Read more
Anonymization and the Future of Data Science
Managing data privacy is becoming an increasingly difficult challenge for massive corporations littered with data silos. New data regulations–from the EU to the US to China— illustrate that this challenge is really just beginning. This trend underscores the importance of anonymization – one of the most important tools in a... Read more
Cognitive Machine Learning (2): Uncertain Thoughts
She pined in thought,  And with a green and yellow melancholy She sat like Patience on a monument,  Smiling at grief. Was not this love indeed? [King Lear, Act 2, Scene 4, Line 117]   In King Lear, Shakespeare stirs a sense of self-consciousness by invoking Patience, sitting up high; isolated in her thoughts;... Read more
How NOT to program the TensorFlow Graph
Using TensorFlow from Python is like using Python to program another computer. Some Python statements build your TensorFlow program, some Python statements execute that program, and of course some Python statements aren’t involved with TensorFlow at all. Being thoughtful about the graphs you construct can help you avoid confusion and... Read more
Streaming Video Analysis in Python
This was originally posted on the Silicon Valley Data Science blog by authors Matthew Rubashkin Data Engineer at SVDS, and Colin Higgins, Data Scientist at Vevo. At SVDS we have analyzed Caltrain delays in an effort to use real time, publicly available data to improve Caltrain arrival predictions. However, the station-arrival time... Read more
Cognitive Machine Learning (1): Learning to Explain
Above is an image of the Zaamenkomst panel: one of the best remaining exemplars of rock art from the San people of Southern Africa. As soon as you see it, you are inevitably herded, like the eland in the scene, through a series of thoughts. Does it have a meaning?  Why are the eland running? What... Read more
ftfy (fixes text for you) 4.4 and 5.0
ftfy is Luminoso’s open-source Unicode-fixing library for Python. Luminoso’s biggest open-source project is ConceptNet, but we also use this blog to provide updates on our other open-source projects. And among these projects, ftfy is certainly the most widely used. It solves a problem a lot of people have with “no... Read more

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