Saturday, August 28, 2021

Machine Learning for Industrial Engineering - Introduction and Bibliography

 

Machine Learning for Mass Production and Industrial Engineering



Machine Learning Methods


• Polynomial regression (ridge)

• Spline regression

• Gaussian process regression (GPR)

Ø radial basis function (RBF)

Ø rational quadratic

• Support vector regression (SVR)

Ø radial basis function (RBF)

Ø quadratic

Machine Learning for Mass Production and Industrial Engineering

Dissertation



11 Most Common Machine Learning Algorithms Explained in a Nutshell
A summary of common machine learning algorithms.
Soner Yıldırım
Soner YILDIRIM
@snr14
Data science | Machine Learning | Python | B.S. in EE, Texas A&M 
https://twitter.com/snr14
https://www.linkedin.com/in/soneryildirim/
Jul 26, 2020

https://www.dataquest.io/blog/top-10-machine-learning-algorithms-for-beginners/

https://www.analyticsvidhya.com/blog/2017/09/common-machine-learning-algorithms/

https://www.researchgate.net/publication/321063821_A_Comparative_Study_on_Machine_Learning_Classification_Models_for_Activity_Recognition
Mohsen Nabian
Journal of Information Technology & Software Engineering, 2017,  7:4

Machine Learning with MATLAB


https://in.mathworks.com/solutions/machine-learning/resources.html   - Videos

How AI Can Improve Product Designs and Designer Performance

July 21, 2021
MIE Assistant Professor Mohsen Moghaddam is the PI of a $614K NSF grant.

This project investigates design processes where the unmet needs of users are elicited from social media, online forums, and e-commerce platforms, and translated into new concept recommendations for designers using artificial intelligence (AI). The motivation stems from the growing abundance of user-generated feedback and a lack of advanced computational methods for drawing useful design knowledge and insights from that data.



Machine Learning Crash Course
with TensorFlow APIs
Google's fast-paced, practical introduction to machine learning

A self-study guide for aspiring machine learning practitioners
Machine Learning Crash Course features a series of lessons with video lectures, real-world case studies, and hands-on practice exercises.
15 hours


Ud  28 Aug 2021,  2 August 2021
Pub 22 July 2021

















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