“In this tutorial I’ll be covering a very important concept in Lua: metatables. Knowledge of how to use metatables will allow you to be much more powerful in your use of Lua. Every table can have a metatable attached to it. A metatable is a table which, with some certain keys set, can change the behaviour of the table it’s attached to…”
“The following links point to a set of tutorials on many aspects of statistical data mining, including the foundations of probability, the foundations of statistical data analysis, and most of the classic machine learning and data mining algorithms.
These include classification algorithms such as decision trees, neural nets, Bayesian classifiers, Support Vector Machines and cased-based (aka non-parametric) learning. They include regression algorithms such as multivariate polynomial regression, MARS, Locally Weighted Regression, GMDH and neural nets. And they include other data mining operations such as clustering (mixture models, k-means and hierarchical), Bayesian networks and Reinforcement Learning…”
“A Bloom filter is a data structure designed to tell you, rapidly and memory-efficiently, whether an element is present in a set. The price paid for this efficiency is that a Bloom filter is a probabilistic data structure: it tells us that the element either definitely is not in the set or may be in the set. The base data structure of a Bloom filter is a Bit Vector…”
“One old good friend of mine, whom I respect a lot and who is a very good C++ programmer, recently asked me to give him an example of how it’s possible make new language features in Lisp. He’s aware of Lisp’s ability to invent new syntax, and he’s also excited about C++11. So he wonders how is that possible to introduce new syntax into your language all by yourself, without having to wait for the committee to adopt the new feature.
I decided to write this article for C++ programmers, explaining core Lisp ideas. It’s a suicide; I’m sure as heck that I’ll fail. Great number of excellent publications on Lisp for beginners exist, and still there are people who cannot grasp what’s so special about it.
Nevertheless, I decided to try. Yet another article with introduction to Lisp won’t harm anybody, nor will it make Lisp even less popular. Let’s be honest: nobody reads this blog, anyway. :)…”
“What follows is a fairly thorough introduction to the library. I chose to break it into three parts as I felt it was too long and daunting as one.
Part 1: Intro to pandas data structures, covers the basics of the library’s two main data structures – Series and DataFrames.
Part 2: Working with DataFrames, dives a bit deeper into the functionality of DataFrames. It shows how to inspect, select, filter, merge, combine, and group your data.
Part 3: Using pandas with the MovieLens dataset, applies the learnings of the first two parts in order to answer a few basic analysis questions about the MovieLens ratings data…”