To support the transition to electronic tagging for sheep and goats, on-farm workshops were conducted across the state with industry representatives as guest speakers who gave demonstrations of the potential of the equipment and technology for flock management, productivity improvements and profit maximisation. For any producers who missed a workshop in their region, here is a recording of the Stockyard Hill workshop.
Lecture 4 introduces single and multilayer neural networks, and how they can be used for classification purposes.
Key phrases: Neural networks. Forward computation. Backward propagation. Neuron Units. Max-margin Loss. Gradient checks. Xavier parameter initialization. Learning rates. Adagrad.
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Natural Language Processing with Deep Learning
Instructors:
- Chris Manning
- Richard Socher
Natural language processing (NLP) deals with the key artificial intelligence technology of understanding complex human language communication. This lecture series provides a thorough introduction to the cutting-edge research in deep learning applied to NLP, an approach that has recently obtained very high performance across many different NLP tasks including question answering and machine translation. It emphasizes how to implement, train, debug, visualize, and design neural network models, covering the main technologies of word vectors, feed-forward models, recurrent neural networks, recursive neural networks, convolutional neural networks, and recent models involving a memory component.
For additional learning opportunities please visit:
https://stanfordonline.stanford.edu/