azymnis

import com.twitter.algebird.{Aggregator, Semigroup}
import com.twitter.scalding._

import scala.util.Random

/**
 * This job is a tutorial of sorts for scalding's Execution[T] abstraction.
 * It is a simple implementation of Lloyd's algorithm for k-means on 2D data.
 *
 * http://en.wikipedia.org/wiki/K-means_clustering

rmoff

Kibana 3 against ElasticSearch 1.4 throws an Connection Failed screen. The error text says to set http.cors.allow-origin, but it misses out the important http.cors.enabled: true

Working config:

$ grep cors elasticsearch-1.4.0.Beta1/config/elasticsearch.yml
http.cors.allow-origin: "/.*/"
http.cors.enabled: true

• Ref
• Ref

debasishg

1. Feature Learning

• Learning Feature Representations with K-means by Adam Coates and Andrew Y. Ng
• The devil is in the details: an evaluation of recent feature encoding methods by Chatfield et. al.
• Emergence of Object-Selective Features in Unsupervised Feature Learning by Coates, Ng
• Scaling Learning Algorithms towards AI Benjio & LeCun
• A Theory of Feature Learning by Brendan van Rooyen, Robert C. Williamson

2. Deep Learning

• Dropout: A Simple Way to Prevent Neural Networks from Overfitting by Nitish Srivastava, Geoffrey Hinton, Alex Krizhevsky, Ilya Sutskever and Ruslan Salakhutdinov
• [Understanding

debasishg

1. Courses and MOOCs

• Introduction to Convex Optimization MITOCW by Prof. Stephen Boyd
• Convex Analysis and Optimization MITOCW by Prof. Dimitri Bertsekas
• Convex Optimization MOOC from Stanford Online
• Convex Optimization at CMU Spring 2015

2. Books

• Convex Optimization – Boyd and Vandenberghe - downloadable book
• Convex Optimization Theory - by Dimitri P. Bertsekas
• Theory of Convex Optimization for Machine Learning - download

syhw

"""
A deep neural network with or w/o dropout in one file.

License: Do What The Fuck You Want to Public License http://www.wtfpl.net/
"""

import numpy, theano, sys, math
from theano import tensor as T
from theano import shared
from theano.tensor.shared_randomstreams import RandomStreams

staltz

The introduction to Reactive Programming you've been missing

(by @andrestaltz)

---

This tutorial as a series of videos

If you prefer to watch video tutorials with live-coding, then check out this series I recorded with the same contents as in this article: Egghead.io - Introduction to Reactive Programming.

---

JamesMGreene

Initialize

gitflow	git
git flow init	git init
	git commit --allow-empty -m "Initial commit"
	git checkout -b develop master

Connect to the remote repository

thigm85

require(ggplot2)

# Figure 1
ggplot(GermanCredit, aes(x = Class)) + 
  geom_bar(aes(y = (..count..)/sum(..count..))) +
  labs(y = "prob.")

stormpython

Data Visualization with Elasticsearch Aggregations and D3

Link to the Elasticsearch Blog.

jprante

mysql> select * from ack;
+------+---------------------+------+
| n    | t                   | c    |
+------+---------------------+------+
|    1 | 2014-01-31 23:37:00 |    6 |
|    2 | 2014-01-31 23:38:00 |    6 |
|    3 | 2014-01-31 23:39:00 |    6 |
+------+---------------------+------+
3 rows in set (0.00 sec)