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    Multi-Layer Neural Network Implementation

    Posted By: ELK1nG
    Multi-Layer Neural Network Implementation

    Multi-Layer Neural Network Implementation
    Published 12/2023
    MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
    Language: English | Size: 546.70 MB | Duration: 1h 30m

    Mathematics of Multi-Layer Neural Network Training and Testing and Implementation in C#

    What you'll learn

    Basic theory of Multi-Layer Neural Networks

    The mathematics of Neural Network Training: Backpropagation and Gradient Descent

    The mathematics of Neuron Activation Functions

    How to implement in C# the Training and Testing of a Multi-Layer Neural Network

    How to create Datasets for Training and Testing the Neural Network

    Requirements

    Basic understanding of Linear Algebra

    Intermediate proficiency in C#

    Basic knowledge of JSON

    Description

    This course presents in detail the implementation of multi-layer neural network training and testing. The steps involved in neural network training and testing are discussed in detail with thorough review of the mathematics. The C# source code, that is available for download, is discussed in detail.  Testing with datasets is presented with the aim of being applicable to any prediction problem use case.  The course begins with a thorough introduction to neural networks, provides a detailed view of the structure of multi-layer neural networks, presents the mathematics involved in neural network training in a very simple and methodical approach, presents the demonstration of testing with a number of datasets, and ends with a quick summary of neural network training.What you will learn in the CourseBasic theory of Multi-Layer Neural NetworksThe mathematics of Neural Network Training: Backpropagation and Gradient DescentThe mathematics of Neuron Activation FunctionsThe process for training and testing the Neural NetworkHow to implement in C# the Training and Testing of a Multi-Layer Neural NetworkHow to create Datasets for Training and Testing the Neural NetworkCourse OutlineSection 1: IntroductionCourse OverviewIntroduction to Neural NetworksMulti-Layer Neural Network StructureSection 2: Mathematics of Neural Network TrainingMulti-Layer Neural Network TrainingSection 3: ImplementationTraining ProcessTesting ProcessAnalysis of the Source CodeSection 4: DatasetsTesting with DatasetsSection 5: SummaryQuick ReviewSection 6: ExerciseExercise

    Overview

    Section 1: Introduction

    Lecture 1 Course Overview

    Lecture 2 Introduction to Neural Networks

    Lecture 3 Multi-Layer Neural Network Structure

    Section 2: Mathematics of Neural Network Training

    Lecture 4 Multi-Layer Neural Network Training

    Section 3: Implementation

    Lecture 5 Training Process

    Lecture 6 Testing Process

    Lecture 7 Analysis of the Source Code

    Section 4: Datasets

    Lecture 8 Testing with Datasets

    Section 5: Summary

    Lecture 9 Quick Review

    Section 6: Exercise

    Lecture 10 Exercise

    IT Professionals and Software Engineers who want to understand the mathematics and implementation of Multi-Layer Neural Networks