A practical guide to deep learning – Tess Ferrandez-Norlander

Machine Learning is one of the fastest growing areas of computer science, and Deep Learning (neural networks) is growing even faster, with lots of data and computing power at our fingertips.

This talk is a practical (very little math) guide to computer vision and deep learning.

We will look at a deep learning project from start to finish, look at how to program and train a neural network and gradually refine it using some tips and tricks that you can steal for your future deep learning projects.

Tess is a developer/data scientist working at Microsoft. Over the past 20 years she has changed the way we do .NET debugging, developed a large number of mobile apps. As of a couple of years ago she moved into the world of data science and machine learning working with a lot of the largest companies in Europe and beyond on really tough ML problems.

She has has spoken at lots and lots of conferences around the world on a wide variety of topics including deep .net debugging, UX, web development and Machine Learning.

Source: NDC Conferences

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