GithubHelp home page GithubHelp logo

dulybina / machine-learning Goto Github PK

View Code? Open in Web Editor NEW

This project forked from georgetown-analytics/machine-learning

0.0 1.0 0.0 37.08 MB

Code & Data for Introduction to Machine Learning with Scikit-Learn

License: MIT License

Python 2.69% Jupyter Notebook 97.31%

machine-learning's Introduction

Introduction to Machine Learning with Scikit-Learn

Code & Data for Introduction to Machine Learning with Scikit-Learn

Scikit-Learn Cheat Sheet

Installing Scikit-Learn with pip

See the full installation instructions for more details; these are provided for convenience only.

Scikit-Learn requires:

  • Python >= 2.6 or >= 3.3
  • Numpy >= 1.6.1
  • SciPy >= 0.9

Once you have installed pip (the python package manager):

Mac OS X

This should be super easy:

pip install -U numpy scipy scikit-learn

Now just wait! Also, you have no excuse not to do this in a virtualenv.

Windows

Install numpy and scipy with their official installers. You can then use PyPi to install scikit-learn:

pip install -U scikit-learn

If you're having trouble, consider one of the unofficial windows installers or anacondas (see the Scikit-Learn page for more).

Ubuntu Linux

Unfortunately there are no official binary packages for Linux. First install the build dependencies:

sudo apt-get install build-essential python-dev python-setuptools \
    python-numpy python-scipy \
    libatlas-dev libatlas3gf-base

Then you can build (hopefully) Scikit-learn with pip:

pip install --user --install-option="--prefix=" -U scikit-learn

Keep in mind however, that there are other dependencies and might be issues with ATLAS and BLAS - see the official installation for more.

machine-learning's People

Contributors

aarora79 avatar agdestine avatar bbengfort avatar drewkwheatley avatar dulybina avatar erblinm avatar jahaas avatar jamesachan avatar jhboyle avatar jstyczynski avatar kbelita avatar kostas1601 avatar mmallampalli avatar nd1 avatar pbwitt avatar rebeccabilbro avatar

Watchers

 avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    ๐Ÿ–– Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. ๐Ÿ“Š๐Ÿ“ˆ๐ŸŽ‰

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google โค๏ธ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.