Remove 2016 Remove Deep Learning Remove Supervised Learning
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How to tackle lack of data: an overview on transfer learning

Data Science Blog

1, Data is the new oil, but labeled data might be closer to it Even though we have been in the 3rd AI boom and machine learning is showing concrete effectiveness at a commercial level, after the first two AI booms we are facing a problem: lack of labeled data or data themselves.

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AI 101: A beginner’s guide to the basics of artificial intelligence

Dataconomy

Undetectable backdoors can be implemented in any ML algorithm Machine learning Machine learning is a subfield of artificial intelligence that focuses on the development of algorithms and models that can learn from data and make predictions or decisions.

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Explosion in 2017: Our Year in Review

Explosion

We founded Explosion in October 2016, so this was our first full calendar year in operation. Highlights included: Developed new deep learning models for text classification, parsing, tagging, and NER with near state-of-the-art accuracy. We set ourselves ambitious goals this year, and we’re very happy with how we achieved them.

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Interactive Fleet Learning

BAIR

These robots use recent advances in deep learning to operate autonomously in unstructured environments. By pooling data from all robots in the fleet, the entire fleet can efficiently learn from the experience of each individual robot. training of large models) to the cloud via the Internet.