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Advanced Machine Learning with ENCOG

Course Summary

In this course you will learn advanced topics related to machine learning for more accurate neural network predictive models. You will also learn different types of neural networks and their implementations using open source machine learning framework ENCOG.


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    Course Syllabus

    Course Introduction
    - 12m 23s

    —Introduction 3m 16s
    —Course Scope 1m 41s
    —Course Structure 2m 22s
    —Quick Recap 4m 18s
    —Summary 0m 46s
    Network Tuning - Part 1
    - 1h 11m

    —Introduction 1m 25s
    —Outline 0m 56s
    —Network Tuning 2m 39s
    —Underfitting And Overfitting 5m 7s
    —Selection of Layers and Neurons 5m 9s
    —Why Network Pruning? 2m 49s
    —About Pruning 1m 2s
    —ENCOG Support for Pruning 3m 25s
    —Training, Cross Validation and Test Dataset 2m 23s
    —Demo Introduction 3m 16s
    —Demo: XAML Code 9m 21s
    —Demo: Core Steps-Shuffle, Segregate, Normalize and Prune 13m 31s
    —Demo: Core Steps-Train 11m 13s
    —Demo: Observations 7m 47s
    —Summary 1m 37s
    Network Tuning - Part 2
    - 40m 32s
    Neural Network Architectures Overview
    - 13m 47s
    Feed Forward Network - Part 1
    - 34m 17s
    Feed Forward Network - Part 2
    - 43m 8s
    Feedback Networks
    - 28m 41s
    Course Summary
    - 6m 48s


Course Fee:
USD 29

Course Type:

Self-Study

Course Status:

Active

Workload:

1 - 4 hours / week

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