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All Blog Posts Tagged 'Learning' (194)

Self-learning Machines & Deep Convolutional Neural Networks Classify Scenes & Identify Objects

Recent research using deep convolutional neural networks and new system architectures have demonstrated the ability of smart machines to autonomously learn to classify image scenes and identify…

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Added by Michael Walker on May 16, 2015 at 2:38pm — 1 Comment

Evaluating RF for Survival Analysis Using Prediction Error Curves

Ulla B. Mogensen, Hemant Ishwaran, Thomas A. Gerds (2012). Evaluating Random Forests for Survival Analysis Using Prediction Error Curves. Journal of Statistical Software, 50(11), 1-23.



Abstract Prediction error curves are increasingly used to assess and compare predictions in survival analysis. This article surveys the R package pec which provides a set of functions for efficient computation of prediction error…
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Added by Diego Marinho de Oliveira on April 10, 2015 at 12:21am — No Comments

Tuning Machine Learning Models Using the Caret R Package

Machine learning algorithms are parameterized so that they can be best adapted for a given problem. A difficulty is that configuring an algorithm for a given problem can be a project in and of itself.

Like selecting ‘the best’ algorithm for a problem you cannot know before hand which algorithm parameters will be best for a problem. The best thing to do is to investigate empirically with controlled experiments.

The caret R package was designed to make finding…

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Added by Diego Marinho de Oliveira on April 7, 2015 at 6:41am — No Comments

Building an NCAA Men’s Basketball Predictive Model

Authors:  / Gregory J. Matthews.

Journal of Quantitative Analysis in Sports. Volume 11, Issue 1, Pages 5–12.



Abstract
 Computing and machine learning advancements have led to the creation of many cutting-edge predictive algorithms, some of which have been demonstrated to provide more accurate forecasts…
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Added by Diego Marinho de Oliveira on April 7, 2015 at 12:46am — No Comments

Implementing a Distributed Deep Learning Network over Spark

Implementing a Distributed Deep Learning Network over Spark

Authors: Dr. Vijay Srinivas Agneeswaran, Director and Head, Big Data Labs, Impetus {[email protected]}

Ghousia Parveen Taj, Lead Software Engineer, Impetus { [email protected]}

Sai Sagar, Software Engineer, Impetus {[email protected]}

Padma Chitturi, Software Engineer,…

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Added by Dr. Vijay Srinivas Agneeswaran on November 25, 2014 at 1:30am — 6 Comments

Popular Software Skills in Data Science Job postings.

This exercise was done to understand the software skills that are in high demand for Data Science. Analysis was done by extracting the job postings from popular online websites. The findings are interesting. R continues to be the most popular skill, found in 70% of the postings. Python follows as a close second. Surprisingly, in spite all the talk about "Big Data Science", SQL comes up third. This shows that traditional RDBMS still continue to be the base for machine learning work…

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Added by Kumaran Ponnambalam on November 21, 2014 at 1:30pm — 3 Comments

Do you know what is bigger than Big Data?

From episode 10 of my Naked Analyst Channel on YouTube.

I think I do - and it is the ‘appification’ of analytics. What I mean by this is the reduction of a complex analytic activity such as market segmentation, down to a single button on your computer interface. Very much like the…

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Added by Steve Bennett on October 6, 2014 at 2:07pm — 4 Comments

Boosting Algorithms for Better Predictions

Boosting is a supervised learning algorithm based on …

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Added by Michael Walker on January 1, 2014 at 11:30am — 1 Comment

Big Data: An Understanding

We establish understanding of things in terms of Data or it will be better to say in terms of Big Data, the utilization of things, matters, issues, inventions, surroundings, maps and much more throughout our everyday life cycle, all of which has a certain data type to get input, process and output for us. Sometime we understand these in almost no time as a human, where data is being originated, what are we targeting for and more, and there are times, when some thing might take longer…

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Added by Atif Farid Mohammad on November 29, 2013 at 12:50am — No Comments

Python Scikit-learn to simplify Machine learning : { Bag of words } To [ TF-IDF ]

Text (word) analysis and tokenized text modeling always give a chill air around ears, specially when you are new to machine learning. Thanks to Python and its extended libraries for its warm support around text analytics and machine learning. Scikit-learn is a savior and excellent support in text processing when you also understand some of the concept like "Bag of word", "Clustering" and "vectorization". Vectorization is  must-to-know technique for all machine leaning learners, text miner…

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Added by Manish Bhoge on September 25, 2013 at 9:47am — No Comments

Tool for Computing Continuous Distributed Representations of Words

Natural language processing (NLP) involves machine learning, artificial intelligence, algorithms and linguistics related to interactions between computers and human languages. One important goal…

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Added by Michael Walker on August 20, 2013 at 7:27pm — No Comments

Data Science Summer Reading List 2013

Machine Learning: A Probabilistic Perspective, by Kevin Murphy.



Boosting: Foundations and Algorithms, by Robert E. Schapire.



Models Behaving Badly: Why Confusing Illusion with Reality Can Lead to Disaster, by Emanuel Derman.



Doing Data Science, by Cathy O'Neil and Rachel…

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Added by Michael Walker on July 9, 2013 at 3:00pm — 1 Comment

M2M + Big Data Analytics = Unlocking Blue Ocean Opportunities at the intersect

M2M + Big Data Analytics = Unlocking Blue Ocean Opportunities at the intersect

When human beings got connected, it unlocked a whole new set of possibilities and companies like facebook, linkedin etc came up with solutions which had never been there before.

The ability of machines to interact with each other promises to unlock a whole new set of opportunities unprecedented in our history

What are some real life examples of M2M…

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Added by derick.jose on July 1, 2013 at 5:40am — 1 Comment

Automatically deskew before machine learning in R

I found it odd there was no way to automatically deskew data in R, so I wrote a short little function to do it.  It noticeably improves the peformance of linear models and linear support vector machines.
http://technicaltidbit.blogspot.com/2013/03/automatically-deskew-before-machine.html

Added by Michael Malak on March 9, 2013 at 2:00pm — 1 Comment

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