Dataiku is proud to participate at the next New York Data Science Meetup, organised by Michael Tamir (Chief Data Scientist and instructor at Galvanize, Personagraph and General Assembly) and Jared Polivka (Chief Evangelist on Data Science at Galvanize).
One of our very talented data scientists, Henri Dwyer, will be speaking in front of many passionate data scientists.
Here goes a little heads up for the evening’s program:
Henri will discuss predictive maintenance - determining the condition of equipment that is currently in use, and predicting when and why equipment is likely to fail.
First, Henri will describe the key concepts in predictive maintenance, as well as some its applications. Next, he will build a workflow using data from the PHM society data challenge, showing how one can use DSS to go from raw data to the final predictions.
Henri will highlight how to avoid common pitfalls, give examples with Data Science Studio of what features can be engineered, what techniques and models can be used to ultimately come up with a robust predictive maintenance model.
Michael Tamir will talk about "Text Understanding, Word2Vec, and Neural Networks”
Supervised text classification is hampered by the need to acquire expensive labeled training sets. By leveraging algorithms similar to Word2Vec and other neural network based text embedding algorithms, one can create vector representations of documents that enable a model to be successfully trained with a drastically reduced training set.
By using this technique the implementer can now devote low investment to acquiring a small volume of labeled data examples in order to train proximity thresholds, without devoting significant resources using traditional text classification algorithms which typically require training volume examples that are orders of magnitude larger.
We look forward to seeing many of you on August 18th!
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