Are you looking for the best statistical learning theory and applications? Based on expert reviews, we ranked them. We've listed our top-ranked picks, including the top-selling statistical learning theory and applications.
We Recommended:
- Hardcover Book
- James, Gareth (Author)
- English (Publication Language)
- 622 Pages - 07/30/2021 (Publication Date) - Springer (Publisher)
- Language Published: English
- Binding: Hardcover
- Comes in Good condition
- Hardcover Book
- Hastie, Trevor (Author)
- This book presents some of the most important modeling and prediction techniques, along with relevant applications
- Topics include linear regression, classification, re-sampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering,...
- Since the goal of this textbook is to facilitate the use of these statistical learning techniques by practitioners in science, industry, and other...
- Hardcover Book
- James, Gareth (Author)
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- Publishing, AI (Author)
- English (Publication Language)
- 188 Pages - 04/18/2020 (Publication Date) - AI Publishing (Publisher)
- Amazon Kindle Edition
- Kahneman, Daniel (Author)
- English (Publication Language)
- 521 Pages - 05/18/2021 (Publication Date) - Little, Brown and Company (Publisher)
- Color graphing Calculator with High resolution LCD display (over 65, 000 colors)
- Natural textbook display
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- Amazon Kindle Edition
- Frost, Jim (Author)
- English (Publication Language)
- 257 Pages - 08/14/2020 (Publication Date) - Statistics By Jim Publishing (Publisher)
- Amazon Kindle Edition
- McGrayne, Sharon Bertsch (Author)
- English (Publication Language)
- 335 Pages - 05/17/2011 (Publication Date) - Yale University Press (Publisher)
- High-resolution, full-color backlit display
- Rechargeable battery
- Preloaded apps and images.Fourteen interactive zoom features
- MathPrint feature.Seven different graph styles for differentiating the look of each graph drawn
- Available in a variety of fun colors, Customers may receive python version while supplies last.
- Amazon Kindle Edition
- Davies, Tilman M. (Author)
- English (Publication Language)
- 833 Pages - 07/16/2016 (Publication Date) - No Starch Press (Publisher)
- Geometric IQ Game: Endless possibilities for kids adults building blocks, not only limited to the instructions, but also try to figure out more...
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- Hyndman, Rob J (Author)
- English (Publication Language)
- 442 Pages - 05/31/2021 (Publication Date) - Otexts (Publisher)
- Hardcover Book
- McElreath, Richard (Author)
- English (Publication Language)
- 612 Pages - 03/16/2020 (Publication Date) - Chapman and Hall/CRC (Publisher)
- Jansen, Stefan (Author)
- English (Publication Language)
- 820 Pages - 07/31/2020 (Publication Date) - Packt Publishing (Publisher)
- Hardcover Book
- Jung, Alexander (Author)
- English (Publication Language)
- 229 Pages - 04/13/2022 (Publication Date) - Springer (Publisher)
- Amazon Kindle Edition
- Domingos, Pedro (Author)
- English (Publication Language)
- 354 Pages - 09/22/2015 (Publication Date) - Basic Books (Publisher)
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- Vegetarian, Dairy free, Soy free, and contains No Gluten Ingredients. This product is third-party tested and manufactured in the USA.
- Amazon Kindle Edition
- Mack, Andrew (Author)
- English (Publication Language)
- 150 Pages - 02/29/2020 (Publication Date)
- Publishing, AI (Author)
- English (Publication Language)
- 128 Pages - 02/08/2020 (Publication Date) - AI Publishing (Publisher)
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FAQ:
Q: What are the class times for statistical learning theory and applications?
A: Statistical Learning Theory and Applications Class Times: Monday and Wednesday 10:30-12:00 Units: 3-0-9 H,G Location: 46-5193 Instructors: Tomaso Poggio (TP), Lorenzo Rosasco (LR), Charlie Frogner (CF), Guille D. Canas (GJ) Office Hours: Friday 1-2 pm in 46-5156, CBCL lounge Email Contact : 9.520@mit.edu 9.520 in 2012 Saturday, February 4, 2012
Q: Is statistical learning theory a mess?
A: •Statistical learning theory is a mess Saturday, February 4, 2012 Overview of overview •Context for this course: a golden age for new AI and the key role of Machine Learning •Success stories from past research in Machine Learning: examples of engineering applications •Statistical Learning Theory
Q: How can optimization theory be useful for machine learning?
A: Concepts from optimization theory useful for machine learning are covered in some detail (first order methods, proximal/splitting techniques…). The final part of the course will focus on deep learning networks. It will introduce a theoretical framework connecting the computations within the layers of deep learning networks to kernel machines.
Q: What is the best book on the mathematics of learning?
A: The Mathematics of Learning: Dealing with Data, Notices American Mathematical Society (AMS), 2003 Poggio, T., R. Rifkin, S. Mukherjee and P. Niyogi. General Conditions for Predictivity in Learning Theory, Nature, 2004 Brunelli, R. and T. Poggio.