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 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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