Introduction to Deep Learning
Big Data & Analytics
This session will introduce Deep Learning concepts, with a focus on image recognition and image location exercises. After a brief introduction to the motivating factors - and why we cannot always just rely on the fantastic Cognitive Services -, concepts such as convolution, pooling and rectified linear units will be presented, so at the end of the session the attendant will be able to understand why deep learning is relevant in 'day to day projects', learn about the development cycle of deep learning models and some techniques as partial checkpoint training.
At the end of the session, a couple of less traditional models (autoencoders and LSTM) will be discussed and cases will be analyzed.
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