The State of the Art in Deep Learning - JHB


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The State of the Art in Deep Learning
Benchmarks in every machine learning task from image classification to machine translation and voice-to-text are bing shattered by Deep Learning. This talk is a quick crash-course on Deep Learning. We will cover the essential theory and some state-of-the-art model architectures to show how the building blocks of deep learning can be composed in a near infinite number of ways to solve an incredible variety of problems.
We will cover computer vision, natural language processing, and speech examples and go through some sample code in a jupyter notebook. Beginners welcome!
About Alex
Alex is the founder and lead data scientist of NumberBoost, a startup that solves problems using deep learning. He previously worked as a quant for a hedge fund and as a data scientist for Superbalist.com. He has an honours degree in actuarial science and currently writing a Statistics MSc focused on machine learning. He is one of the organizers of the Cape Town Deep Learning meet-up. He has given talks on deep learning at PyConZA, PyConDE, and a number of other conferences.
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The State of the Art in Deep Learning - JHB