Data is big
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Data is big
"The future is here. It's just not evenly distributed yet." William Gibson
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Webscope | Yahoo Labs

Webscope | Yahoo Labs | Data is big | Scoop.it
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We have various types of data available to share. They are categorized into Ratings, Language, Graph, Advertising and Market Data, Computing Systems and an appendix of other relevant data and resources available via the Yahoo Developer Network.

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Cheatsheet for dplyr join functions (#rstats)

Cheatsheet for dplyr join functions (#rstats) | Data is big | Scoop.it
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Expert Big Data Tips

Whether you are interested in healthcare data analytics or looking to get started with big data and marketing, these fundamental principles from data experts w…
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In-depth introduction to machine learning in 15 hours of expert videos

In-depth introduction to machine learning in 15 hours of expert videos | Data is big | Scoop.it
In January 2014, Stanford University professors Trevor Hastie and Rob Tibshirani (authors of the legendary Elements of Statistical Learning textbook) taught an online course based on their newest textbook, An Introduction to Statistical Learning with Applications in R (ISLR). I found it to be an excellent course in statistical learning...
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Graphs R Cool - RNeo4j tutorial

Graphs R Cool - RNeo4j tutorial | Data is big | Scoop.it
RNeo4j combines the power of a Neo4j graph database with the R statistical programming language to easily build predictive models based on connected data. From calculating the probability of friends of friends connections to plotting an adjacency heat…
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Recommender Systems (Machine Learning Summer School 2014 @ CMU)

Slides for my 4 hour tutorial on Recommender Systems at the 2014 Machine Learning School at CMU
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Edu-Videos | 100 Most Popular Machine Learning Talks at VideoLectures.Net

Edu-Videos | 100 Most Popular Machine Learning Talks at VideoLectures.Net | Data is big | Scoop.it
Machine learning is a subfield of computer science and artificial intelligence that deals with the construction and study of systems that can learn from data, rather than follow only explicitly pro...
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Mining of Massive Datasets

Mining of Massive Datasets | Data is big | Scoop.it
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The book is based on Stanford Computer Science course CS246: Mining Massive Datasets (and CS345A: Data Mining).

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So you wanna try Deep Learning? - Exchangeable random experiments

So you wanna try Deep Learning? - Exchangeable random experiments | Data is big | Scoop.it
I’m keeping this post quick and dirty, but at least it’s out there. The gist of this post is that I put out a one file gist that does all the basics …
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Max Kuhn Interviewed by DataScience.LA at useR - YouTube

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Data Scientist, Author ("Applied Predictive Modeling" with Kjell Johnson) and R caret package developer Max Kuhn sits down for an in-depth interview with Eduardo Arino de la Rubia. They discuss the art and science of Predictive Modeling in the real world, the multifaceted R caret package, the pluses and perils of programming in R and much more.

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First-person Hyperlapse Videos

First-person Hyperlapse Videos | Data is big | Scoop.it
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Algo for turning boring first-person perspective videos into the attractive time lapses.
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Markov Chains #visualization

Markov chains, named after Andrey Markov, are mathematical systems that hop from one "state" (a situation or set of values) to another. For example, if you made a Markov chain model of a baby's behavior, you might include "playing," "eating", "sleeping," and "crying" as states, which together with other behaviors could form a 'state space': a list of all possible states. In addition, on top of the state space, a Markov chain tells you the probabilitiy of hopping, or "transitioning," from one state to any other state---e.g., the chance that a baby currently playing will fall asleep in the next five minutes without crying first.

ukituki's insight:

Markov chains, named after Andrey Markov, are mathematical systems that hop from one "state" (a situation or set of values) to another. For example, if you made a Markov chain model of a baby's behavior, you might include "playing," "eating", "sleeping," and "crying" as states, which together with other behaviors could form a 'state space': a list of all possible states. In addition, on top of the state space, a Markov chain tells you the probabilitiy of hopping, or "transitioning," from one state to any other state---e.g., the chance that a baby currently playing will fall asleep in the next five minutes without crying first.

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Learning more like a human: 18 free eBooks on Machine Learning

Learning more like a human: 18 free eBooks on Machine Learning | Data is big | Scoop.it

Machine Learning is a type of artificial intelligence (AI) that provides computer programs with the ability to learn, grow and change when exposed to new data, without being explicitly programmed. Here, we present 20 free eBooks on Machine Learning, which will guide you to understand more about Machine Learning.

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Big Data Frameworks

Big Data Frameworks | Data is big | Scoop.it
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“Big-data” is one of the most inflated buzzword of the last years. Technologies born to handle huge datasets and overcome limits of previous products are gaining popularity outside the research environment. The following list would be a reference of this world. It’s still incomplete and always will be.

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Data wrangling, exploration, and analysis with R

Data wrangling, exploration, and analysis with R | Data is big | Scoop.it

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ukituki's insight:

Learn how to

explore, groom, visualize, and analyze data,make all of that reproducible, reusable, and shareableusing R
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Learn R : 12 Books and Online Resources - YOU CANalytics

Learn R : 12 Books and Online Resources - YOU CANalytics | Data is big | Scoop.it
R, an open-source statistical and data mining programming language, is slowly but surely catching up in its race with commercial software like SAS & SPSS. I believe R will eventually replace SAS as the language of choice for modeling and analysis for most organizations. The primary reason for this is plainly commercial. Most organizations areRead More...
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Using data science to build better products

Using data science to build better products | Data is big | Scoop.it
Data science is about extracting knowledge from data and creating practical, actionable insights to improve some facet of a business

Via Carla Gentry CSPO
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Carla Gentry CSPO's curator insight, September 23, 6:16 AM

Making sure that data insights are useful to people who don't think about machine learning all day is super important, since the beneficiary of data science work is often a front-line employee, a customer/user or another non-technical stakeholder. For this reason--at least for us at Yhat--data science and product-building go hand-in-hand. Sure, we're data junkies and enjoy walking the parameter space as much as the next guy or girl. But the kicker for us in any data analysis project is the "why".

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Tutorials | KDD 2014, Data Mining for Social Good

20th ACM SIGKDD Conference on Knowledge Discovery and Data Mining: homepage
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Siri’s Inventors Are Building a Radical New AI That Does Anything You Ask | Enterprise | WIRED

Siri’s Inventors Are Building a Radical New AI That Does Anything You Ask | Enterprise | WIRED | Data is big | Scoop.it
Viv was named after the Latin root meaning live. Its San Jose, California, offices are decorated with tchotchkes bearing the numbers six and five (VI and V in roman numerals). Ariel Zambelich When Apple announced the iPhone 4S on October 4, 2011, the headlines were not about its speedy A5 chip or improved camera. Instead…
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R packages - Book in progress

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This is the in-progress book site for “R packages”. It will be published with O’Reilly around June 2015.

 

Packages are the fundamental units of reproducible R code. They include reusable R functions, the documentation that describes how to use them, and sample data. In this section you’ll learn how to turn your code into packages that others can easily download and use. Writing a package can seem overwhelming at first. So start with the basics and improve it over time. It doesn’t matter if your first version isn’t perfect as long as the next version is better

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Machine Learning Algorithm Studying Fine Art Paintings Sees Things Art Historians Had Never Noticed

Machine Learning Algorithm Studying Fine Art Paintings Sees Things Art Historians Had Never Noticed | Data is big | Scoop.it
Artificial intelligence reveals previously unrecognised influences between great artists
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Harvard Unleashes Swarm of Robots

Harvard Unleashes Swarm of Robots | Data is big | Scoop.it
Harvard University scientists have developed a thousand tiny robots that, like swarming bees or army ants, can work together in vast numbers without a guiding central intelligence, in the largest team so far of self-organizing mobile robots. Photo: Michael Rubenstein, Harvard University.
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A Conversation with Hadley Wickham – the useR! 2014 interview

A Conversation with Hadley Wickham – the useR! 2014 interview | Data is big | Scoop.it
Hadley Wickham is famous. He’s not Kardashian famous, but walking around useR! and seeing the community’s reaction to him, there’s no question, he’s ‘R famous’.
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Learning from the best Kagglers

Learning from the best Kagglers | Data is big | Scoop.it
Guest contributor David Kofoed Wind is a PhD student in Cognitive Systems at The Technical University of Denmark (DTU): As a part of my master's thesis on competitive machine learning, I talked to ...
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Deep Learning in Neural Networks: An Overview

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In recent years, deep artificial neural networks (including recurrent ones) have won numerous contests in pattern recognition and machine learning. This historical survey compactly summarises relevant work, much of it from the previous millennium. Shallow and deep learners are distinguished by the depth of their credit assignment paths, which are chains of possibly learnable, causal links between actions and effects. I review deep supervised learning (also recapitulating the history of backpropagation), unsupervised learning, reinforcement learning & evolutionary computation, and indirect search for short programs encoding deep and large networks.
  
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