mickaellegal/The-Nature-of-Code-Examples
Repository for example code from The Nature of Code book
Discovered public repositories for mickaellegal in the GitHub catalog.
Repository for example code from The Nature of Code book
Actions in Launch Center Pro to create quick entries in Day One
A Machine Learning library based on Theano
Documents and Code for the Machine Learning Class by Andrew Ng
Collection of interesting open datasets that I find on the web
A collection of my iPython Notebooks
A simple book recommender built with flask. Model deployed on yhat and application deployed on Heroku.
Little web app that classifies your text based on a corpus of New York Times articles.
Code from HackerRank Challenges
An easy-to-use Flask template for Heroku.
Heroku environment variable configurations for Flask.
Tutorial deployment of a flask app on Heroku
Predicting the popularity of articles on the web
A sdk for AlchemyAPI using Python
Public repository.
Machine learning workshop using Python, pandas, and scikit-learn. The first half of the day covered supervised classification using Logistic Regression and how to use cross validation to evaluate your models . The second half of the day covered unsupervised clustering with Kmeans as well as an overview of the data science process.
It's a presentation framework based on the power of CSS3 transforms and transitions in modern browsers and inspired by the idea behind prezi.com.
The HTML Presentation Framework
scikit-learn: machine learning in Python
Translating R Data Analyses to Python
Data-Intensive Text Processing with MapReduce
A JavaScript visualization library for HTML and SVG.
A Gentle Introduction to SQL Using SQLite
Script for downloading Coursera.org videos and naming them.
Simple Libraries to access Rdio's Web API
aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)
This is a collaborative attempt to define what belongs in a data science curriculum to productively advance the field forward. Fork this repo and submit pull requests if you would like to contribute (or open an issue)