mbsariyildiz

def pairwise_dist (A, B):  
  """
  Computes pairwise distances between each elements of A and each elements of B.

  Args:
    A,    [m,d] matrix
    B,    [n,d] matrix

  Returns:
    D,    [m,n] matrix of pairwise distances

mrtzh

"""Visualize stability of stochastic gradient descent for finding a linear
separator."""

import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt

np.random.seed(1)
mpl.rcParams['axes.linewidth'] = 0.0

patik

Squashing Git Commits

The easy and flexible way

This method avoids merge conflicts if you have periodically pulled master into your branch. It also gives you the opportunity to squash into more than 1 commit, or to re-arrange your code into completely different commits (e.g. if you ended up working on three different features but the commits were not consecutive).

Note: You cannot use this method if you intend to open a pull request to merge your feature branch. This method requires committing directly to master.

Switch to the master branch and make sure you are up to date:

thebucknerlife

#Simple Authentication with Bcrypt

This tutorial is for adding authentication to a vanilla Ruby on Rails app using Bcrypt and has_secure_password.

The steps below are based on Ryan Bates's approach from Railscast #250 Authentication from Scratch (revised).

You can see the final source code here: repo. I began with a stock rails app using rails new gif_vault

##Steps

blackfalcon

Git-workflow vs feature branching

When working with Git, there are two prevailing workflows are Git workflow and feature branches. IMHO, being more of a subscriber to continuous integration, I feel that the feature branch workflow is better suited, and the focus of this article.

If you are new to Git and Git-workflows, I suggest reading the atlassian.com Git Workflow article in addition to this as there is more detail there than presented here.

I admit, using Bash in the command line with the standard configuration leaves a bit to be desired when it comes to awareness of state. A tool that I suggest using follows these instructions on setting up GIT Bash autocompletion. This tool will assist you to better visualize the state of a branc

coreylynch

import itertools

import numpy as np

from sklearn.linear_model import SGDClassifier, SGDRanking
from sklearn import metrics
from minirank.compat import RankSVM as MinirankSVM
from scipy import stats

bwhite

"""Information Retrieval metrics

Useful Resources:
http://www.cs.utexas.edu/~mooney/ir-course/slides/Evaluation.ppt
http://www.nii.ac.jp/TechReports/05-014E.pdf
http://www.stanford.edu/class/cs276/handouts/EvaluationNew-handout-6-per.pdf
http://hal.archives-ouvertes.fr/docs/00/72/67/60/PDF/07-busa-fekete.pdf
Learning to Rank for Information Retrieval (Tie-Yan Liu)
"""
import numpy as np

agramfort

"""
Implementation of pairwise ranking using scikit-learn LinearSVC

Reference: "Large Margin Rank Boundaries for Ordinal Regression", R. Herbrich,
    T. Graepel, K. Obermayer.

Authors: Fabian Pedregosa <fabian@fseoane.net>
         Alexandre Gramfort <alexandre.gramfort@inria.fr>
"""

fabianp

"""
Implementation of pairwise ranking using scikit-learn LinearSVC

Reference: 

    "Large Margin Rank Boundaries for Ordinal Regression", R. Herbrich,
    T. Graepel, K. Obermayer 1999

    "Learning to rank from medical imaging data." Pedregosa, Fabian, et al., 
    Machine Learning in Medical Imaging 2012.

lrvick

from geventwebsocket.handler import WebSocketHandler
from gevent.pywsgi import WSGIServer
from flask import Flask, request, render_template

app = Flask(__name__)

@app.route('/')
def index():
    return render_template('index.html')