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R: The most powerful and most widely used statistical software

In the last ten years, the open source R statistics language has exploded in popularity and functionality, emerging as the data scientist's tool of choice.

 

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Data is big
&amp;amp;quot;The future is here. It's just not evenly distributed yet.&amp;amp;quot; - William Gibson     :::: Follow this topic for fresh resources and ideas related to Data Science, Machine Learning, Algorithms and #bigdata :::: <a href="http://www.dataisbig.co" rel="nofollow">http://www.dataisbig.co</a>/
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Deep Learning with Python (PyData Seattle 2015)

Deep Learning with Python: Getting started and getting from ideas to insights in minutes. PyData Seattle 2015 Alex Korbonits (@korbonits)
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How to Create NBA Shot Charts in Python

How to Create NBA Shot Charts in Python | Data is big | Scoop.it
In this post I go over how to extract a player's shot chart data and then plot it using matplotlib and seaborn.
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The complete catalog of argument variations of select() in dplyr

The complete catalog of argument variations of select() in dplyr | Data is big | Scoop.it

# Data preparation ------------------------------------------------------------------
library(dplyr)

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The Unreasonable Effectiveness of Recurrent Neural Networks

The Unreasonable Effectiveness of Recurrent Neural Networks | Data is big | Scoop.it
Musings of a Computer Scientist.
ukituki's insight:

We've learned about RNNs, how they work, why they have become a big deal, we've trained an RNN character-level language model on several fun datasets, and we've seen where RNNs are going. You can confidently expect a large amount of innovation in the space of RNNs, and I believe they will become a pervasive and critical component to intelligent systems.

 

  
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List of amazing talks from New York R Conference 2015

List of amazing talks from New York R Conference 2015 | Data is big | Scoop.it
From NewYork R conference 2015, here is a list of amazing videos which describes about various application of R i.e. statistics, machine learning
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Text Mining of The Complete Works of Jane Austen

Text Mining of The Complete Works of Jane Austen | Data is big | Scoop.it
Text mining refers to extraction of meaningful information from qualitative and unstructured text data. In this document we will perform text mining on The Complete Works of Jane Austen. We can tak...
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Microservices, containers, and machine learning

http://www.oscon.com/open-source-2015/public/schedule/detail/41579 In this presentation, an open source developer community considers itself algorithmically. T…
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15 Easy Solutions To Your Data Frame Problems In R

15 Easy Solutions To Your Data Frame Problems In R | Data is big | Scoop.it
Discover how to create a data frame in R, change column and row names, access values, attach data frames, apply functions and much more.
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Streamgraphs in R

Streamgraphs in R | Data is big | Scoop.it

It's not easy to visualize a quantity that varies over time and which is composed of more than two subsegments. Take, for example, this stacked bar chart of religious affiliation of the Australian population, by time: While it's easy to see the how the share of Anglicans (at the bottom of the chart) has changed over time, it's much more difficult to assess the change in the "No religion" category: the separated bars coupled with the (necessarily) uneven positioning makes it hard to judge changes from year to year. 

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15 Questions All R Users Have About Plots

15 Questions All R Users Have About Plots | Data is big | Scoop.it
There are different types of R plots, ranging from the basic graph types to complex types of graphs. Here we discover how to create these.
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The Data Incubator - 7 week training in #datascience

A 7 week fellowship training and placing advanced-degree data scientists and quants.
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R tutorial on the Apply family of functions

R tutorial on the Apply family of functions | Data is big | Scoop.it
Introduction In our previous tutorial Loops in R: Usage and Alternatives , we discussed one of the most important constructs in programming: the loop.  Eventually we deprecated the usage of loops in R in favor of vectorized functions. In this post we highlight some of the most used vectorized functions: the apply functions.  
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Demis Hassabis (CEO, DeepMind Technologies) - The Theory of Everything and AI learning to play Atari games

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Machine Learning Class 2015 - University of Oxford

Machine Learning Class 2015 - University of Oxford | Data is big | Scoop.it
Website for the Department of Computer Science at the heart of computing and related interdisciplinary activity at Oxford.
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Strategies To Speed Up R Code

Strategies To Speed Up R Code | Data is big | Scoop.it
The for-loop in R, can be very slow in its raw un-optimised form, especially when dealing with larger data sets. There are a number of ways you can make your logics run fast, but you will be really surprised how fast you can actually go.
This chapter shows a number of approaches including simple
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Sparkling Water Applications Meetup 07.21.15

Michal Malohlava's Sparkling Water Applications Meetup on 07.21.15, focusing on the Ask Craig use case. http://h2o.ai/blog/2015/06/ask-craig-sparkling-water/
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GitHub Special: Data Scientists to Follow & Best Tutorials on GitHub

GitHub Special: Data Scientists to Follow & Best Tutorials on GitHub | Data is big | Scoop.it
GitHub has some of the most awesome collections of data science resources. This article provides this list and people to follow on GitHub
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