Learning From Data, Problem 1.7

This post is a solution to the problem taken from Abu-Mostafa, Yaser S., Malik Magdon-Ismail, and Hsuan-Tien Lin. Learning from data. Vol. 4. New York, NY, USA:: AMLBook, 2012.. Quoted text refers to the original problem statement, verbatim. For more solutions, see Consider leaving a Star if this helps you. A sample of heads and tails is created by tossing a coin a number of times independently. Assume we have a number of coins that generate different samples independently.

Handling Time-series in Pandas and Numpy.

Here we will show you how to properly use the Python Data Analysis Library (pandas) and numpy. The agenda is: How to load data from csv files The basic pandas objects: DataFrames and Series Handling Time-Series data Resampling (optional) From pandas to numpy Simple Linear Regression Consider leaving a Star if this helps you. The following ipython magic (this is literally the name) will enable plots made by matplotlib to be rendered inside this notebook.

A Report on the Ziggurat Method

Mathematical proof of functionality, of a highly efficient pseudo-random number generator: The Ziggurat Method

Ad hoc Big Data Analysis with Dask

How can we keep the simplicity and power of pandas, while extending it to be out-of-core and parallel?