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Predictive with R  Topic with Python


Predictive Modeling Using R

“Predictive modeling leverages statistics to predict outcomes”


“Predictive modeling is a name given to a collection of mathematical techniques having in common the goal of finding a mathematical relationship between a target, response, or “dependent” variable and various predictor or “independent” variables with the goal in mind of measuring future values of those predictors and inserting them into the mathematical relationship to predict future values of the target variable.”

Introduction to Predictive Modeling with Examples – SAS Global Forum 2012


Below, From the Simplilearn ‘Business Analytics foundation – R Tools course is a thorough, highly rated and watched (26k+ views)

Topic Modeling Using Python

A Topic model, in machine learning and natural language processing, is a type of statistical model for discovering the abstract “topics” that occur in a collection of documents.


Podcast: O’Reilly – Topic models: Past, present, and future

From O’Reilly…Ben Lorica sits down with David Blei, co-author of the seminal paper on topic models, and who remains one of the leading researchers in the field. We talked about the origins of topic models, their applications, improvements to the underlying algorithms, and his new role in training data scientists at Columbia University.

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Topic Modeling with Python.
Below is a recent video of Christine Doig, a data scientist at Continuum Analytics. “The talk will go through the full topic modeling pipeline: from different ways of tokenizing your document, to using the Python library gensim, to visualizing your results and understanding how to evaluate them.”



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Blog Publisher / Head of Data Science Search

Founder & Head of Data Science Search at Starbridge Partners, LLC.