Introduction-Syllabus
Syllabus
Introduction-Welcome
Welcome
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Introduction-Neural Networks, Deep Learning, and TensorFlow
Introduction to TensorFlow
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TensorFlow 2.x and Eager Execution
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Labs in This Course
Introduction to Deep Learning
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Deep Neural Networks
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Supervised Learning Models-Convolutional Neural Networks
Introduction to Convolutional Neural Networks (CNNs)
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Convolutional Neural Networks (CNNs) for Classification
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Convolutional Neural Networks (CNNs) Architecture
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Supervised Learning Models (Cont'd)-Recurrent Neural Networks
The Sequential Problem
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Recurrent Neural Networks (RNNs)
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The Long Short Term Memory (LSTM) Model
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Language Modelling
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Unsupervised Deep Learning Models-Restricted Boltzmann Machines
Introduction to Restricted Boltzmann Machines
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Restricted Boltzmann Machines (RBMs)
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Unsupervised Deep Learning Models (Cont'd) and scaling-Autoencoders
Introduction to Autoencoders
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Autoencoders
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Unsupervised Deep Learning Models (Cont'd) and scaling-Scaling (optional)
Scaling of neural networks