Neural Networks

Machine Learning

Collection: 
openAcademy
Author: 
Yaser Abu Mostafa
Year: 
2014
Conditions of Use: 
Attribution-NonCommercial-ShareAlike 3.0 Unported
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Description: 
This is an introductory course on machine learning that covers the basic theory, algorithms, and applications. Machine learning (ML) enables computational systems to adaptively improve their performance with experience accumulated from the observed data. ML techniques are widely applied in engineering, science, finance, and commerce to build systems for which we do not have full mathematical specification (and that covers a lot of systems). The course balances theory and practice, and covers the mathematical as well as the heuristic aspects.

Machine Learning

Collection: 
openAcademy
Author: 
Andrew Ng
Year: 
2014
Conditions of Use: 
Attribution-NonCommercial-ShareAlike 3.0 Unported
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Description: 
This course is offered by Stanford as an online course for credit. It can be taken individually, or as part of a master’s degree or graduate certificate earned online through the Stanford Center for Professional Development.

This course provides a broad introduction to machine learning and statistical pattern recognition.

Topics include: supervised learning (generative/discriminative learning, parametric/non-parametric learning, neural networks, support vector machines); unsupervised learning (clustering, dimensionality reduction, kernel methods); learning theory (bias/variance tradeoffs; VC theory; large margins); reinforcement learning and adaptive control.

Machine Learning (Pedro Domingos)

Collection: 
Coursera
Author: 
Pedro Domingos
Year: 
0
Conditions of Use: 
Coursera grants you a personal license to access and use the Sites. You may download material only for your own personal, non-commercial use. You may not copy, reproduce, retransmit, distribute, publish, commercially exploit or transfer material.
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Machine Learning (Andrew Ng)

Collection: 
Coursera
Author: 
Andrew Ng
Conditions of Use: 
Coursera grants you a personal license to access and use the Sites. You may download material only for your own personal, non-commercial use. You may not copy, reproduce, retransmit, distribute, publish, commercially exploit or transfer material.
Media Format: 
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Artificial Intelligence (Roslina Rashid)

Collection: 
Individual Authors
Author: 
Roslina BT Rashid
Year: 
2011
Conditions of Use: 
Attribution-NonCommercial-ShareAlike 3.0 Unported
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Description: 
This introduction course of Artificial Intelligence (AI) will explain the meaning of AI and elaborate the most popular and frequently used Artificial Intelligence technologies. Application of AI technologies in chemical and bioprocess field will be explored. This course will also introduce a simple programming of AI using MATLAB. This course employs Cooperative Learning and self directed learning.

Soft Computing (RC Chakraborty)

Collection: 
Individual Authors
Author: 
RC Chakraborty
Year: 
2010
Media Format: 
Material Type: 
Description: 
Soft computing topics covered. Introduction to soft computing, fundamentals of neural network, back propagation network, associative memory adaptive resonance theory, fuzzy set theory, fuzzy systems, genetic algorithms and modeling and hybrid systems.

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