SimpleAI, Artificial Intelligence with python

SimpleAI is an easy to use lib implementing in python many of the
artificial intelligence algorithms described on the book "Artificial
Ingelligence, a Modern Approach", from Stuart Russel and Peter Norvig.

This implementation takes some of the ideas from the Norvig's
implementation (the aima-python lib), but it's made with a more
"pythonic" approach, and more emphasis on creating a stable, modern,
and mantenible version. We are testing the majority of the lib, it's
available via pip install, has a standard repository and lib architecture,
well documented, respects the python pep8 guidelines, provides only
working code (no placeholders for future things), etc. Even the
internal code is written with readability in mind, not only the
external API.

This new release adds a few statistical classification methods to SIMPLEAI with
the intention of start replicating the machine learning aspects of aima-python.

There is a special focus in decision tree learning, where three different
methods for decision tree learning are added, with one of them following
strictly the aima pseudo-code, being particularly useful for teaching.
The other classifiers added are Naive Bayes and K-Nearest Neighbors.

This release also includes lots of tests for the classifiers, documentation,
and a few sample uses of the classifiers

Quepy is a framework to transform questions in natural language into queries in a database language.

We are sharing an open source framework that we made here at

Quepy is a framework to transform questions in natural language into
queries in a database language.
It can be easily adapted to different types of questions in natural
language, so that with little code you can build your own interface to
a database in natural language.

Currently, Quepy supports only the SPARQL query language, but in
future versions and with the collaboration of the community we are
planning to extend it to other database query languages.

You are invited to participate and collaborate with the project.

We leave here links to the documentation [0], the source code [1], and
also a Pypi package [2].

Also, as an example, we have an online instance of Quepy the interacts
with DBpedia available [3].

Source code for this example instance is available within the Quepy
package so you can kickstart your project from an existing, working

If you like it, or if you have suggestions: Tell us about it! We're
just an email away [4].


[3] (Don't expect a QA system, it's an example)
[4] quepyproject[(at)]

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