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Data is big
"The future is here. It's just not evenly distributed yet." William Gibson
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Strata 2014: Geoffrey Moore, "Crossing the Chasm: What's New, What's Not"

Strata 2014: Geoffrey Moore, "Crossing the Chasm: What's New, What's Not" | Data is big | Scoop.it

http://strataconf.com/strata2014/public/schedule/detail/33761  ;

 

Crossing the Chasm has been a key reference point for high-tech marketing since its publication in 1990, but a lot has changed since then, especially with the rise of cloud computing, software as a service, mobile endpoints, big data analytics, and viral marketing. This has led author Geoff Moore to produce a revised edition, released on January 28, with all new examples taken from the last decade and two new appendices to help bridge the gap between what's new and what's not. Join Geoff as he highlights lessons learned in bringing disruptive innovations to market in the 21st century.

ukituki's insight:

#BigData is still in the era of a cool tools: Let's take #Python, #Shark, #Giraph and #Go after the #Pig. 

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Jay Falker, Peter Norvig, Director of Research, Google

Jay Falker, Peter Norvig, Director of Research, Googleon NIAC2014 on Livestream - Watch live streaming Internet TV. Broadcast your own live streaming videos, like NIAC2014 in Widescreen HD. Livestream, Be There.
ukituki's insight:

Peter Norvig's talk "Live and Learn, How Big Data and Machine Learning Power the Internet" starts around 21 min.

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Stanford scientists put free text-analysis tool on the web

Stanford scientists put free text-analysis tool on the web | Data is big | Scoop.it
ukituki's insight:
Now anyone can drag and drop text into a linguistic analysis tool powered by machine learning.

Ever wondered whether a certain TV show had a slant in favor of a political candidate?

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Top 11 Free Software for Text Analysis, Text Mining, Text Analytics - Predictive Analytics Today

Top 11 Free Software for Text Analysis, Text Mining, Text Analytics - Predictive Analytics Today | Data is big | Scoop.it
Review of Top 11 Free Software for Text Analysis, Text Mining, Text Analytics ? KH Coder, Carrot2, GATE, tm, Gensim, Natural Language Toolkit, RapidMiner, Unstructured Information Management Architecture, OpenNLP, KNIME, Orange-Textable and LPU are some of the key vendors who provides text analytics software
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knitr in a knutshell

ukituki's insight:

KnitR is a really important tool for reproducible research. You create documents that are a mixture of text and code; when processed through KnitR, the code is replaced by the results and/or figures produced.

 
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Princeton’s guide to linear modeling and logistic regression with R

Princeton’s guide to linear modeling and logistic regression with R | Data is big | Scoop.it
If you're new to the R language but keen to get started with linear modeling or logistic regression in the language, take a look at this "Introduction to R" PDF, by Princeton's Germán Rodríguez. (There's also a browsable HTML version.) In a crisp 35 pages it begins by taking you through the basics of R: simple objects, importing data, and graphics. Then, it works through several examples of linear models (formula basics, fitting a model, model diagnostics, analysis of variance and even regression spones). 
ukituki's insight:

In a crisp 35 pages it begins by taking you through the basics of R: simple objects, importing data, and graphics. Then, it works through several examples of linear models (formula basics, fitting a model, model diagnostics, analysis of variance and even regression spones). Finally, there's a section on Generalized Linear Models, with a focus on logistic regression. The document doesn't attempt to explain all of the capabilities of R, but instead works through a series of examples to teach by demonstration. All of the datasets used in the guide are available online, so it's easy to follow along from home

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6 Video Tutorials And Playlists on Machine Learning!

6 Video Tutorials And Playlists on Machine Learning! | Data is big | Scoop.it
These tutorials will be helpful for newbies as well as pros. Check them out!
ukituki's insight:

Are you fascinated by robots? Well, these 'toys' may be astonishing for many but are complicated structures from within and require a lot of hard work. If you too are planning to kick start your career in robotics or if you are already studying and require some resources, here we bring some help with 6 video turorials and playlists on Machine Learning! Happy Robotics!

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Producing Simple Graphs with R

Producing Simple Graphs with R | Data is big | Scoop.it
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word2vec - Tool for computing continuous distributed representations of words.

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This tool provides an efficient implementation of the continuous bag-of-words and skip-gram architectures for computing vector representations of words. These representations can be subsequently used in many natural language processing applications and for further research.

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13 Forecasting Resources

13 Forecasting Resources | Data is big | Scoop.it
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Time series course

These are the slides from a course on Time series forecasting using R. Each lecture lasted one hour.

Introduction to forecasting [Exercises]The forecaster's toolbox [Exercises]Autocorrelation and seasonality [Exercises]White noise and time series decomposition [Exercises]Exponential smoothing methods [Exercises]ETS models [Exercises]Transformations and adjustments [Exercises]Stationarity and differencing [Exercises]Non-seasonal ARIMA models [Exercises]Seasonal ARIMA models [Exercises]Dynamic regression [Exercises]Advanced methods
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Machine Learning Lesson of the Day - Cross-Validation

Machine Learning Lesson of the Day - Cross-Validation | Data is big | Scoop.it
Validation is a good way to assess the predictive accuracy of a supervised learning algorithm, and the rule of thumb of using 70% of the data for training and 30% of the data for validation general...
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Clarifying various terms for evaluating classifier (or hypothesis testing) performance

Clarifying various terms for evaluating classifier (or hypothesis testing) performance | Data is big | Scoop.it
This post first appeared here. I thank Prof. Alex Hartemink for the extremely neat summary. Terms true positives: TP true negatives: TN false positives: FP (type I error) false negatives: FN (type ...
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Interpreting Model Performance with Cost Functions

Interpreting Model Performance with Cost Functions | Data is big | Scoop.it
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Machine Learning and Data Mining Books - A Baker's Dozen for Data Scientists

Machine Learning and Data Mining Books - A Baker's Dozen for Data Scientists | Data is big | Scoop.it
Here are 13 books on Machine Learning and Data Mining that are great resources, references, and refreshers for Data Scientists. (This is definitely a small sel…
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The Transformation Series: Paul McDonald of Google Consumer Surveys - YouTube

The Transformation Series: Paul McDonald of Google Consumer Surveys - YouTube | Data is big | Scoop.it
ukituki's insight:

An indepth conversation with Paul McDonald of Google Consumer Surveys on where they have been, what's in store for 2014 and how GCS is evolving to deliver more impact and value to consumers, researchers and other Google products.

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etcML - easy text classification with Machine Learning

Do you want to know if your favorite sports team is popular on Twitter? Or if your kickstarter proposal is written for success? With a few simple clicks, etcML can make these kinds of classifications and many others. You can train our machine learning algorithms for your own tasks and share your classifier with others!
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Visualizing Models

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Transcendent Man 720 PTBR

Transcendent Man 720 PTBR | Data is big | Scoop.it
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Documentary about Ray Kurzweil

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IBM Research Accelerating Discovery: Social Analytics - YouTube

IBM Research Accelerating Discovery: Social Analytics - YouTube | Data is big | Scoop.it
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DARPA Open Catalog

DARPA Open Catalog | Data is big | Scoop.it
DARPA Open Catalog contains a curated list of DARPA-sponsored software and peer-reviewed publications. DARPA funds fundamental and applied research in a variety of areas including data science, cyber, anomaly detection, etc., which may lead to experimental results and reusable technology designed to benefit multiple government domains.
ukituki's insight:
This is quite a big deal
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Deep Learning for Image Understanding in Bing

Deep Learning for Image Understanding in Bing | Data is big | Scoop.it
ukituki's insight:

A few months ago we provided a behind the scenes look into how Bing is improving image search quality. In this post we wanted to take the opportunity to further that discussion highlighting some recent outreach we did with researchers to explore new approaches to improving image search quality. My colleague Eason Wang will give you a closer look at how we are taking advantage of Deep Learning and entity understanding to deliver more relevant, useful and beautiful image results in Bing.

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Deep Learning in Practice: Word2vec Tutorial by @RadimRehurek

Deep Learning in Practice: Word2vec Tutorial by @RadimRehurek | Data is big | Scoop.it
I never got round to writing a tutorial on how to use word2vec in gensim. It s simple enough and the API docs are straightforward, but I know some people prefer more verbose formats. Let this post be a tutorial and a reference example.
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Visualizing K-Means Clustering

Visualizing K-Means Clustering | Data is big | Scoop.it
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60+ R resources to improve your data skills

60+ R resources to improve your data skills | Data is big | Scoop.it
From books to videos to online tutorials -- most free! -- here are plenty of ideas to burnish your R knowledge.
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luiy's curator insight, January 17, 1:07 PM

These websites, videos, blogs, social media / communities, software andbooks/ebooks can help you do more with R; the favorites are listed in bold.

 

 

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Online data sources for analaysis

List of data sets and data set sources Sample data sets for machine learning Data sets for predictive modeling and visualizations Economic and Social Data sets
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