Machine Learning PrincipalThoughtWorks
Mat is a research engineer who is currently a principal consultant for machine learning at ThoughtWorks. He previously worked on joint Google Brain/X projects in the area of both reinforcement learning robotics and a number of natural language understanding tasks. Prior to Google he worked at Wavii as well as Amazon Web Services working on very large data processing systems. During his 20 years as a software engineer he has gathered broad experience covering everything from front end development to building petabyte scale data pipelines working in a mix of startups and large corporations.
Talks I've Given
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Self supervised learning & making use of unlabelled data.
Featuring Mat Kelcey
The general supervised learning problem starts with a labelled dataset. It's common though to additionally have a large collection of unlabelled data also. Self supervision techniques are a way to make use of this data to boost performance. In this talk we'll review some contrastive learning...
machine-learning-ai -
Practical Learning To Learn
Featuring Mat Kelcey
Gradient descent continues to be our main work horse for training neural networks. One recurring problem though is the large amount of data required. Meta learning frames the problem not as learning from a single large dataset, but learning how to learn from multiple related smaller datasets. In...
ai-&-ml