Open Access
Subscription Access
A Review on Machine Learning:Trends and Future Prospects
Machine learning addresses the question of how to build computers that improve automatically through experience. It is one of today’s most rapidly growing technical fields, lying at the intersection of computer science and statistics, and at the core of artificial intelligence and data science. Recent progress in machine learning has been driven both by the development of new learning algorithms and theory and by the ongoing explosion in the availability of online data and low-cost computation. The adoption of data-intensive machine-learning methods can be found throughout science, technology and commerce, leading to more evidence-based decision-making across many walks of life, including health care, manufacturing, education, financial modeling, policing, and marketing.
Keywords
Machine, Computer Science, Statics, Technology.
User
Font Size
Information
- Blankertz, G. Dornhege, C. Schafer, R. Krepki, J. Kohlmorgen, K.-R. Muller, V. Kunz-mann, F. Losch, and G. Curio. BCI bit rates and error detection for fast-pace motor commands based on single-trial EEG analysis.IEEE Transactions on Neural Systems and Re-habilitation Engineering, 11:127–131, 2003.
- E. Bauer and R. Kohavi. Empirical comparison of voting classification algorithms: Bagging, boosting and variants.MachineLearning, 36:105–142, 1999.
- A Few Useful Things to Know about Machine Learning Pedro Domingos Department of Computer Science and Engineering University of Washington Seattle, WA .S.A.pedrod@cs.washington.edu.
- Zien, G. Ratsch, S. Mika, B. Scholkopf, T. Lengauer, and K.-R. Muller.Engineering Sup-port Vector Machine Kernels That Recognize Translation Initiation Sites.BioInformatics,16(9):799–807, September 2000.
- Yom-Tov. An introduction to pattern classification. In U. von Luxburg, O. Bousquet, and G. Ratsch, editors, Advanced Lectures on Machine Learning, volume 3176 of LNAI , pages 1–23. Springer, 2004.
- V.N. Vapnik.The nature of statistical learning theory. Springer Verlag, New York, 1995. U. von Luxburg, O. Bousquet, and G. Ratsch, editors.Advanced Lectures on Machine Learning, volume 3176 of LNAI. Springer, 2004 7. A Brief Introduction into Machine Learning Gunnar Ratsch Friedrich Miescher Laboratory of the Max Planck Society, Spemannstraße 37, 72076 Tubingen, Germany.
- Trends in extreme learning machines: a review, by Huang, G., Huang, G., Song, S., & You, K. (2015)
- Machine Learning: A study of algorithms that learn from data and experience.
- A Visual Introduction to Machine Learning (2015). Courtesy of Stephanie yee and Tony Chu
Abstract Views: 222
PDF Views: 0