Solving the Text Labeling challenge with EnsembleLDA and Active Learning

Feb 23, 2019

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Want to build a text classification pipeline and have text with high quality labels that business can act on? Great, throw in a language model, some BiLSTMs and CNNs and viola, you have trained a high-quality classifier. Unfortunately, many text data available for industry projects are unlabeled and difficult to label because of their industry specific nature. The challenge can be split into three parts: 1. Unsupervised Text Exploration – What types of texts are there? 2. Label Curation – Given the texts, which set of labels provides the most business value? 3. Active Labeling/Learning – Which texts should be labeled first/next when human labeling is expensive? This talk shares a few technical stories for solving all three challenges.

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Machines can learn. Incredibly fast. Faster than you. They are getting smarter and smarter every day. They are already changing your world, your business and your life. Artificial intelligence revolution is here. Come and learn how to turn this threat into your biggest opportunity. This is not another academic conference. Our goal is to foster discussion between machine learning practitioners and all people who are interested in applications of modern trends in artificial intelligence. You can look forward to inspiring people, algorithms, data, applications, workshops and a lot of fun during three days as well as at two great parties.

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