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Deep learning 1: Intro to machine learning
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Learn the fundamentals behind state-of-the-art AI
This course equips you with the code, theory and tools you need to implement cutting edge machine teaching algorithms that power today’s state-of-the-art applications. You’ll learn how we can use neural networks to approximate arbitrarily complex input-output relationships, use convolutional neural networks for processing spatially structured data like images, and recurrent neural networks to model data that varies over time, like video.
In this workshop we’ll recap some machine learning fundamentals and the data engineering skills that we’ll need for us to dive into deep learning. Those include gradient based optimisation, logistic and linear regression, regularisation. We’ll also get hands on with industry ready tools like TensorBoard, PyTorch and Tune.
