The answer is 42! Saturday, September 28, 2013. Summer of 2013 with Numpy and Google. I got chance to work as student contributor at Numpy. And the experience was worth paying the amount of effort. I have joined Numpy, the community thats quite friendly and helpful. What I gained this year? The most challen.

In fact, most of the work involved was optimizing the speed of execution, improving readability - this includes proper naming and convenient infrastructure of the code base, and writing a comprehensive documentation.

Musings and ramblings through the world of Python and beyond. In recent months, a host of new tools and packages have been announced for working with data at scale in Python. Talk from the 2015 PyData Seattle. Toolkit to visualize the results on a map.

My personal blog on python and machine learning. This post summarizes the new feature of calibrating predicted probabilities of binary and multi-class classifiers, which has been added in the 0. It gives several examples, which illustrates both the different properties of under-confident and over-confident classifiers, and how to calibrate those such that they become well-calibrated. Advice for applying Machine Learning.

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