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Udemy - Neural Networks Made Easy With Matlab |
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Torrent Details |
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Description |
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Sample Files: None
Video Format: MP4
Video: AVC, 1348x720, 1.85: 1, 15fps, 294kbps
Audio: AAC, 44.1kHz, 85.3kbps, stereo
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. Medium MATLAB (Matrix Laboratory) several paradigms numerical computing environment and the fourth generation programming language designed mathworks. While in MATLAB is intended primarily for numerical computation, but an optional set of tools with MuPAD symbolic engine has access to the symbolic computation capabilities, too. One such tool is the neural network tool. This tool is a free, open source software for the simulation model of the brain and central nervous system, based on MATLAB computing platforms. In these courses you will learn the general principles of neural network toolbox developed in MATLAB and you can use this tool effectively, as well.
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Files in this torrent |
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| FILENAME | SIZE | |
|---|---|---|
 | 1- Chapter 1/1- Introduction.mp4 | 4.4 MB |
| 1- Chapter 1/2- What is in this course .mp4 | 6.2 MB |
| 1- Chapter 1/3- Function Fitting.mp4 | 12 MB |
| 1- Chapter 1/4- Pattern Recognition.mp4 | 18 MB |
| 1- Chapter 1/5- Data Clustering.mp4 | 11 MB |
| 2- Chapter 2/6- Simple Neuron.mp4 | 11.9 MB |
| 2- Chapter 2/7- Network architecture.mp4 | 7.1 MB |
| 2- Chapter 2/8- Data structure.mp4 | 11.7 MB |
| 2- Chapter 2/9- Training style.mp4 | 23.7 MB |
| 3- Chapter 3/10- Neuron Model.mp4 | 23.8 MB |
| 3- Chapter 3/11- Perceptron networks.mp4 | 12.9 MB |
| 3- Chapter 3/12- GUI nntool.mp4 | 11.7 MB |
| 4- Chapter 4/13- Network architecture.mp4 | 8.4 MB |
| 4- Chapter 4/14- Linear filters and linear classification.mp4 | 15.3 MB |
| 5- Chapter 5/15- Introduction to Training Process.mp4 | 12 MB |
| 5- Chapter 5/16- Back Propagation Architecture.mp4 | 13 MB |
| 5- Chapter 5/17- Momentum.mp4 | 7.5 MB |
| 5- Chapter 5/18- Faster learning Heuristic algorithm.mp4 | 13.6 MB |
| 5- Chapter 5/19- Faster training-numerical optimization techniques.mp4 | 17.6 MB |
| 5- Chapter 5/20- Numerical techniques Quasi newton.mp4 | 12.2 MB |
| 5- Chapter 5/21- Numerical techniques Levenberg Marquart.mp4 | 11.4 MB |
| 6- Chapter 6/22- Last Word.mp4 | 1.5 MB |
| 6- Chapter 6/23- Comparison of different training algorithms.mp4 | 36.2 MB |
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