background preloader

Python Data Analysis Library — pandas: Python Data Analysis Library

Python Data Analysis Library — pandas: Python Data Analysis Library
pandas is an open source, BSD-licensed library providing high-performance, easy-to-use data structures and data analysis tools for the Python programming language. 0.13.1 released (February 3, 2014) This is a scheduled bugfix release for 0.13.0, with multiple issues and regressions addressed, and several back-compatible enhancements introduced. See the Release Notes to read all about it. For binaries and source archives of v0.13.1 see the Download page. What problem does pandas solve?

Related:  pythonmachine-learning-coursesitesWWW_addonsBig DataTools/Libraries

80+ Best Free Python Tutorials, eBooks & PDF To Learn Programming Online Thinking of learning Python to make a dent in the universe? We have compiled a huge list of absolutely FREE Python tutorials, eBooks and PDFs to make your life easier. Python has taken over the programming world with a storm and has now become one of the most popular languages.

Machine Learning for Developers by Mike de Waard Most developers these days have heard of machine learning, but when trying to find an 'easy' way into this technique, most people find themselves getting scared off by the abstractness of the concept of Machine Learning and terms as regression, unsupervised learning, Probability Density Function and many other definitions. If one switches to books there are books such as An Introduction to Statistical Learning with Applications in R and Machine Learning for Hackers who use programming language R for their examples. However R is not really a programming language in which one writes programs for everyday use such as is done with for example Java, C#, Scala etc. This is why in this blog machine learning will be introduced using Smile, a machine learning library that can be used both in Java and Scala. These are languages that most developers have seen at least once during their study or career.

Cage Match Greg Jackson, the single most successful trainer in the multi-billion-dollar sport of professional mixed martial arts fighting, works out of a musty old gym in Albuquerque, New Mexico, not far from the base of the Sandia Mountains. On a recent morning, the 38-year-old Jackson, who has the cauliflowered ears and bulbous nose of a career fighter, watched two of his students square off inside the chain-link walls of a blood-splattered ring called the Octagon. One of them was Jon Jones, the light heavyweight champion of the Ultimate Fighting Championship (UFC), the premier MMA league. In four weeks, Jones would be defending his title against Rashad Evans, an expert fighter and his former training partner. Gusto - gusto - What is Gusto? - Gusto is a set of APIs for building intelligent web applications with semantic similarity, collaborative filtering, recommandation, etc. Gusto is a set of APIs for building intelligent web 2.0 applications more easily. Rather than writing your own logic from scratch, you can include Gusto's modules for semantic similarity measures, clustering, collaborative and recommendation functionalities, etc. Gusto is at an early stage, it is aimed to contain of the following modules : Beans : Abstraction of Resources and access to properties Repository : Data services to access and query repositories: databases, semantic repositories etc. Semsim : Semantic similarity calculation between objects Clusterant : Clustering engine Colfil : Collaborative filtering Neighborhood : Services for defining Objects' neighborhoods (similar objects) Recommend : Recommendation engine Evaluation : Module for evaluating the precision of recommendations

Free Python Books You are here: Home Python Learning to Program Using Python [PDF] Machine Learning at Quora - Engineering at Quora - Quora Adapted from my original answer to How does Quora use machine learning in 2015? At Quora we have been using machine learning approaches for some time. We are constantly coming up with new approaches and making big improvements to the existing ones. It is important to note that all these improvements are first optimized and tested offline by using many different kinds of offline metrics but are always finally tested online through A/B tests. In the following paragraphs, I will describe some of the most important applications and techniques of ML at Quora as of 2015.

The Principles of VBD Revisited Want to Dominate your League? Then Dominate your Draft. This article will show you how to do this with the draft system that serious Fantasy Owners across the country use. It's called Value Based Drafting or VBD. Why listen to us about it? machine learning in Python — scikit-learn v0.11 documentation "We use scikit-learn to support leading-edge basic research [...]" "I think it's the most well-designed ML package I've seen so far." "scikit-learn's ease-of-use, performance and overall variety of algorithms implemented has proved invaluable [...]." "For these tasks, we relied on the excellent scikit-learn package for Python." "The great benefit of scikit-learn is its fast learning curve [...]"

Supercharging C++ Code With Embedded Python – EuroPython 2012 Talk « This is the talk that I gave at EuroPython 2012 in Florence, Italy. It was a 60-minute talk, so it’s light on technical details. I am planning to publish follow-up articles that provide step-by-step instructions along with complete code examples.

Related:  Librairies PythonPandasOutils d'analysePython