Outline In this presentation, we present the DNN and CNN structure We briefly shows some famous CNN works (structure, improvements, performance) Difficulty of training DNN and shows a good solution (ResNet) Revised Version [2021-06-25] A revised version can be download from Download_Link Slides [embeddoc url="https://liwen.site/wp-content/uploads/2020/07/Deep-Learning-2-CNN_V12.pptx" download="all" viewer="microsoft"]
Content In the document, we present: Each neural network (NN) consists of many neurons, and each neuron has two elements: linear function and activation function. We have shown the reason of using activation functions. (choices of activation functions) Two numerical examples have been given to track the forward and backward…
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Objectives Deep learning is a recently hot machine learning method. The deep learning architectures are formed by the composition of several nonlinear transformations with the goal to yield more abstract and extract useful representations/features. (i) Start with a revision of the basic principle of Neural Networks, neutron structure, examples of…
Objectives Deep learning is a recently hot machine learning method. The deep learning architectures are formed by the composition of several nonlinear transformations with the goal to yield more abstract and extract useful representations/features. (i) Start with a revision of the basic principle of Neural Networks, neutron structure, examples of…
Objectives Decision trees and random forests have been used in our group for some years. It is good to have a review on its basic theory, limitation and recent developments. The study includes, but not limited to, the definition of decision trees, binary trees, multi-decision trees, ensemble methods, bagging, boosting,…