The primary goal of this talk is twofold: to evaluate the need of data mining and introduce some very cool, simple yet powerful machine learning techniques to audience such as classification, clustering, collaborative filtering, recommendation etc in your Python web applications. This talk will conclude with some explanation and limitations of machine learning algorithms.
Basic knowledge of Python is sufficient. However some experience with Django, meshups, machine learning or data hunger is encouraged. All talk material and django apps will be available after talk.
Everyday we enjoy great experiences when we access websites that help the user in every aspect of interaction. Some web users prefer to get recommendations, suggestions and much faster contextual searches when they access a website or web application. This track talk shows you some great techniques that can be used to better improve website usability and will also include a demonstration with Django.
The goal of this talk is to encourage many web masters, developers or engineers to use the best in analytics that Python has to offer (i.e. NLTK, numpy, scipy, etc.) The richness of python in this area is one no other language can compete with.
Prerequisites to this track talk are knowledge of functional programming in Python, some mathematical concepts (graph theory, statistics) and basic understanding of OOP.
20th–26th June 2011