'Machine learning models' diaporamas de présentation

Action-Perception-Learning Cycles 2012 Fall Graduate Course

Action-Perception-Learning Cycles 2012 Fall Graduate Course. Byoung-Tak Zhang Department of Computer Science and Engineering & Cognitive Science and Brain Science Programs Seoul National University http://bi.snu.ac.kr/. What i s a Learning System?.

645 views • 64 slides

From Data to Deployment: overcoming the challenges of embedding R models in Production

320 views • 32 slides

Machine Learning

Machine Learning. Rob Schapire Princeton Avrim Blum Carnegie Mellon Tommi Jaakkola MIT. Machine Learning: models and basic issues. Avrim Blum Carnegie Mellon University. [NAS Frontiers of Science, 2003]. Machine learning can be used to. recognize speech,

413 views • 28 slides

Machine Learning

Machine Learning. Rob Schapire Princeton Avrim Blum Carnegie Mellon Tommi Jaakkola MIT. Machine Learning: models and basic issues. Avrim Blum Carnegie Mellon University. [NAS Frontiers of Science, 2003]. Machine learning can be used to. recognize speech,

287 views • 28 slides

How do we know if AI is right? Challenges in the testing of AI systems

How do we know if AI is right? Challenges in the testing of AI systems. Jukka K Nurminen Professor Data-Intensive Computing in Natural Sciences jukka.k.nurminen@helsinki.fi. AI Research Focus on Algorithms Less on Testing and Other Real Use Issues.

214 views • 21 slides

Context-based object-class recognition and retrieval by generalized correlograms

Context-based object-class recognition and retrieval by generalized correlograms. by J. Amores, N. Sebe and P. Radeva. Discussion led by Qi An Duke University. Outline. Introduction Overview of the approach Image representation Learning and matching Implementation with boosting

332 views • 20 slides

Data needs cleaning before machine learning can find meaning

Enterprises large and small need to use all means at their disposal to gain a strategic advantage for their business. To remain competitive, these organizations must make use of contemporary machine learning tools to unlock value and meaning from the wealth of data they have about their customers, products, employees, work processes, and even competitors.

32 views • 2 slides