Getting Started
Introduction to Neural Networks
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The Single Input Single Output Neural Network (1:05)
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Coding : Single Input Single Output Neural Network (10:24)
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The Single Input Multiple Output Neural Network (2:30)
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Coding : Single Input Multiple Output Neural Network (10:46)
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The Multiple Input Single Output Neural Network (2:39)
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Coding : Multiple Input Single Output Neural Network (13:11)
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The Multiple Input Multiple Output Neural Network (2:49)
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Coding : Multiple Input Multiple Output Neural Network (17:47)
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The Hidden Layer Neural Network (2:37)
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Coding : The Hidden Layer Neural Network (18:19)
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Comparing and Finding Error (1:53)
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Coding : Finding Error (9:24)
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Understanding data representation in Machine Learning (1:18)
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Understanding the "Learning" in Machine Learning (4:21)
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Coding : Brute-force Learning (17:07)
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Introduction to Gradient Descent (3:16)
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Functional Description of a Biological Neuron (2:08)
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Source Code Download
Introduction to Neural Network (Part 2)
Logistic Regression
Deep Neural Networks
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Internals of a 2 layer Neural Network (3:01)
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Understanding Computational Graphs (8:50)
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Updating Parameters Effectively (3:33)
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Understanding the Importance of Vectorization (9:05)
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Summary of Back-propagation and Forward-propagation (0:40)
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Initializing Parameters Effectively (0:38)
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Understanding Layers and Units (1:12)
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Understanding the Shapes (3:12)
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Understanding Broadcasting in Programming (1:18)
Improving Neural Networks with Regularization Techniques
Building a Complete Neural Network Library for Predicting Handwritten Numbers
Building Our Neural Network Library Utility Functions
Building Our Neural Network Library Engine
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Coding : Implementing the Forward Propagation Function (9:39)
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Coding : Implementing the Back Propagation Function (13:08)
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Coding : Implementing the NNPredict Function (3:23)
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Coding : Implementing the NNBuild and NNTrain Functions (11:17)
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Coding : Implementing the NNSaveModel and NNLoadModel Functions (10:10)
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Coding : Implementing the NNPrint Function (7:11)
Testing our Neural Network Library
Closing
