[Udemy.com] Neural Networks made easy with Matlab [2015, ENG]

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Post 24-Nov-2015 09:15

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Neural Networks made easy with Matlab
Год выпуска: 2015
Производитель: Udemy
Сайт производителя: udemy.com
Автор: Coursovie Training Inc. Isan Zatkar
Продолжительность: 2:00
Тип раздаваемого материала: Видеоклипы
Язык: Английский
Описание: MATLAB (matrix laboratory) is a multi-paradigm numerical computing environment and fourth-generation programming language developed by MathWorks. Although MATLAB is intended primarily for numerical computing, but by optional toolboxes, using the MuPAD symbolic engine, has access to symbolic computing capabilities too. One of these toolboxes is Neural Network toolbox. This toolbox is free, open source software for simulating models of brain and central nervous system, based on MATLAB computational platform. In these courses you will learn the general principles of Neural Network Toolbox designed in Matlab and you will be able to use this Toolbox efficiently as well.
Среде MATLAB (матричные лаборатории) несколько парадигм численных вычислений среда и язык программирования четвертого поколения разработана mathworks. Хотя в MATLAB предназначена в основном для численных вычислений, но необязательных наборов инструментов, с помощью MuPAD символическое двигателя, имеет доступ к возможности символьных вычислений тоже. Одним из таких инструментов является нейросетевого инструментария. Данный инструментарий является свободным, открытым исходным кодом программное обеспечение для моделирования модели мозга и центральной нервной системы, на базе MATLAB вычислительные платформы. На этих курсах вы узнаете общие принципы нейросетевого инструментария разработанный в среде MATLAB и вы сможете использовать данный инструментарий эффективно, как хорошо.

Содержание

Section 1: Chapter 1
Lecture 1
Introduction
Lecture 2
What is in this course ?
Lecture 3
Function Fitting
Lecture 4
Pattern Recognition
Lecture 5
Data Clustering
Section 2: Chapter 2
Lecture 6
Simple Neuron
Lecture 7
Network architecture
Lecture 8
Data structure
Lecture 9
Training style
Section 3: Chapter 3
Lecture 10
Neuron Model
Lecture 11
Perceptron networks
Lecture 12
GUI nntool
Section 4: Chapter 4
Lecture 13
Network architecture
Lecture 14
Linear filters & linear classification
Section 5: Chapter 5
Lecture 15
Introduction to Training Process
Lecture 16
Back Propagation Architecture
Lecture 17
Momentum
Lecture 18
Faster learning_Heuristic algorithm
Lecture 19
Faster training-numerical optimization techniques
Lecture 20
Numerical techniques_Quasi newton
Lecture 21
Numerical techniques_Levenberg_Marquart
Section 6: Chapter 6
Lecture 22
Comparison of different training algorithms
Lecture 23
Last Word
Файлы примеров: отсутствуют
Формат видео: MP4
Видео: AVC, 1348x720, 1.85:1, 15fps, 294kbps
Аудио: AAC, 44.1kHz, 85.3kbps, stereo

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