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...Through a combination of advanced training techniques and neural network architectural components, it is now possible to create neural networks that can handle tabular data, images, text, and audio as both input and output. Deep learning allows a neural network to learn hierarchies of information in a way that is like the function of the human brain. This course will introduce the student to classic neural network structures, Convolution Neural Networks (CNN), Long Short-Term Memory (LSTM), Gated Recurrent Neural Networks (GRU), General Adversarial Networks (GAN) and reinforcement learning. Application of these architectures to computer vision, time series, security, natural language processing (NLP), and data generation will be covered. ...

...Clear organization and self-contained examples make it possible to follow along outside the classroom, using the repo as a self-study resource. For learners and instructors alike, the course provides a coherent path from foundational linguistics to current techniques, with reproducible code that makes concepts concrete.

Strategies make up everything we do. We have thinking strategies that are effective. We have thinking strategies that are less so! It has been proven possible to secure elements of successful strategies and apply these to our training of all kinds of skills. Looking at the practices of successful people, and breaking down the parts of their effective behaviours we can teach these in order to improve particular areas of effectiveness. This is the basis of this learning and teaching strategy!