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Does anyone know of useful resources for Machine Learning. I am interested in learning about Support Vector Machines, preferably in C++?

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 Andrew D Mann, Analyst at Morgan Stanley, Quantitative Finance MSc, BEng Hons. Mechanical Engineering

 Sunday, August 31, 2014

I am looking to expand from my knowledge in genetic programming and move onto an area I hear people discussing on a regular basis, Support Vector Machines. Preferably I would love to find a book that provides practical examples as this allows me to get up and running where I can start to understand the mechanics. If anyone has any good resources in Artificial Intelligence, Genetic Programming or Neural Architecture I would appreciate a heads up! Cheers!


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5 comments on article "Does anyone know of useful resources for Machine Learning. I am interested in learning about Support Vector Machines, preferably in C++?"

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 Wei S., Senior Research Scientist

 Monday, September 1, 2014



Andrew, particular for SVM, Ng's ML course in Coursera is very helpful in explaining it by easy-to-understand videos. Here is the url by my quick search: https://www.coursera.org/course/ml. Not sure if you need to register first in order to view the materials. If you like, I do not mind to share my saved copy. In terms of software package, Scikit-learn has a good implementation for major ML algorithms including SVM.



Hope it helps.



Wei


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 Gordon Dash, Professor, Computational Finance at University of Rhode Island

 Monday, September 1, 2014



You might be interested in the works of my colleague:



http://www.amazon.com/s/ref=nb_sb_noss?url=search-alias%3Daps&field-keywords=hamel%20support%20vector%20machines


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 Andrew D Mann, Analyst at Morgan Stanley, Quantitative Finance MSc, BEng Hons. Mechanical Engineering

 Tuesday, September 2, 2014



Thank you all for your fantastic suggestions!! I am so grateful to you all!


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 Tom Rodde, Managing Director, Axis Corporate USA

 Tuesday, September 2, 2014



Possibly helpful deck, and I'd imagine his presentation at the Trading Show could have been of use. Best of luck, Andrew!



http://www.terrapinn.com/template/Live/PDF/Alexander-Fleiss-of-Rebellion-Research%27s/7185/15051/cmViZWxsaW9uMjAxNC5wZGY=



Alexander Fleiss, President, Chief Investment Officer, and Chairman of Rebellion Research, participated in this year's Trading Show Chicago by giving a presentation on the afternoon of Day One on applying machine learning to global economics.



Download his presentation slides now >



Prior to co-founding Rebellion Research in 2007, Alexander served as a Principal at KMF Partners LP, a long-short US equity fund. While at KMF, he was primarily responsible for investments in the financial service, technology and consumer industries.



Find out what he had to say on:



Approaches to AI


Machine learning advantages


AI vs. human decision making


Overfitting


Model complexity


When to use AI


AI for short-term trading


AI economic predictions


AI predicting in practice


Alexander began his investment career as an analyst for Sloate, Weisman, Murray & Co which was acquired by Neuberger Berman. He developed investment algorithms with the firm's CEO, Laura Sloate, who is a now a partner at Neuberger Berman and was featured in the book Investment Gurus. Alexander received a BA Degree from Amherst College.


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 Ingvar Engelbrecht, CEO, developer, janitor at Nova Data Skr. AB and www.maieutic.com

 Tuesday, September 2, 2014



Biocompsystems.com

Good neural net/genetic algorithm systems and other techniques

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