Demystifying recent advancements in ML to build you a better classification model

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In machine learning, classification problems are one of the most fundamentally exciting and yet challenging existing problems. The implications of a competent classification model are enormous — these models are leveraged for natural language processing text classification, image recognition, data prediction, reinforcement training, and a countless number of further applications.

However, the present implementation of classification algorithms are terrible. During my time at Facebook, I found that the generic solution to any machine learning classification problem was to “throw a gradient descent boosting tree at it and hope for the best”. …

Jeff Da

http://jeffda.com/ Ex-Facebook, Palantir, Expo. University of Washington. NLP, Reinforcement Learning, ML, etc. etc. etc.

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