Libros sobre el tema "Predictive programming"

author, Mayor Eric y Forte Rui Miguel author, eds. R: Predictive analysis : master the art of predictive modeling. Birmingham, UK: Packt Publishing, 2017.

Nitin, Indurkhya y Zhang Tong 1971-, eds. Fundamentals of predictive text mining. London: Springer-Verlag, 2010.

Learning data mining with Python: Harness the power of Python to analyze data and create insightful predictive models. Birmingham, UK: Packt Publishing, 2015.

C, Georgiadis Michael, Pistikopoulos Efstratios N y Dua Vivek, eds. Multi-parametric model-based control: Theory and applications. Weinheim: Wiley-VCH, 2007.

Fahringer, Thomas. Automatic performance prediction of parallel programs. Boston: Kluwer Academic Publishers, 1996.

Hyslop, William F. Performance prediction of relational database management systems. Toronto: Computer Systems Research Institute, University of Toronto, 1991.

Fahringer, Thomas. Automatic Performance Prediction of Parallel Programs. Boston, MA: Springer US, 1996.

R, Horn J. y United States. National Aeronautics and Space Administration. Scientific and Technical Information Division., eds. Geometric programming prediction of design trends for OMV protective structures. [Washington, D.C.]: National Aeronautics and Space Administration, Office of Management, Scientific and Technical Information Division, 1990.

Rauscher, Harold M. The microcomputer scientific software series 4: Testing prediction accuracy. St. Paul, Minn: U.S. Dept. of Agriculture, Forest Service, North Central Forest Experiment Station, 1986.

Brown, Robert Goodell. Smoothing, forecasting and prediction of discrete time series. Mineola, NY: Dover Publications, 2004.

Paul, Bishop y Educational Systems Associates, eds. Adapted physical education: A comprehensive resource manual of definition, assessment, programming and future prediction. Kearney, NE: Educational Systems Associates, Inc., 1988.

United States. National Aeronautics and Space Administration., ed. TBIEM3D: A computer program for predicting ducted fan engine noise. Hampton, Va: National Aeronautics and Space Administration, Langley Research Center, 1997.

D, Dang L., Coats E. E y George C. Marshall Space Flight Center., eds. Engineering and programming manual: Two-dimensional kinetic reference computer program (TDK). Marshall Space Flight Center, Al: George C. Marshall Space Flight Center, 1985.

Kil, David H. Pattern recognition and prediction with applications to signal characterization. Woodbury, N.Y: AIP Press, 1996.

Bernd, Girod, ed. Multi-frame motion-compensated prediction for video transmission. Boston: Kluwer Academic Publishers, 2001.

Matthew, O'Keefe, Kerr Christopher, United States. Dept. of Energy. Office of Biological and Environmental Research. y Goddard Space Flight Center, eds. Second International Workshop on Software Engineering and Code Design in Parallel Meteorological and Oceanographic Applications: Proceedings of a workshop sponsored by the U.S. Department of Energy, Office of Biological and Environmental Research; the Department of Defense, High Performance Computing and Modernization Office; and the NASA Goddard Space Flight Center, Seasonal-to-Interannual Prediction Project, and held at the Camelback Inn, Scottsdale, Arizona, June 15-18, 1998. Greenbelt, Md: National Aeronautics and Space Administration, Goddard Space Flight Center, 1998.

Forte, Rui Miguel. Mastering Predictive Analytics with R. Packt Publishing, Limited, 2015.

Borrelli, Francesco, Alberto Bemporad y Manfred Morari. Predictive Control for Linear and Hybrid Systems. Cambridge University Press, 2017.

Predictive Control for Linear and Hybrid Systems. Cambridge University Press, 2017.

Borrelli, Francesco, Alberto Bemporad y Manfred Morari. Predictive Control for Linear and Hybrid Systems. Cambridge University Press, 2018.

Ammi, Ken. Transhuman Hollywood: From Normative Fiction to Predictive Programming. Independently Published, 2019.

Borrelli, Francesco, Alberto Bemporad y Manfred Morari. Predictive Control for Linear and Hybrid Systems. University of Cambridge ESOL Examinations, 2017.

Mayor, Eric. Learning Predictive Analytics with R. Packt Publishing, Limited, 2015.

Miller, James D. y Rui Miguel Forte. Mastering Predictive Analytics with R - Second Edition. Packt Publishing - ebooks Account, 2017.

Mayor, Eric. Learning Predictive Analytics with R: Get to Grips with Key Data Visualization and Predictive Analytic Skills Using R. Packt Publishing, Limited, 2015.

Learning Predictive Analytics with Python: Gain practical insights into predictive modelling by implementing Predictive Analytics algorithms on public datasets with Python. Packt Publishing, 2016.

Kumar, Ashish. Learning Predictive Analytics with Python: Gain Practical Insights into Predictive Modelling by Implementing Predictive Analytics Algorithms on Public Datasets with Python. Packt Publishing, Limited, 2016.

Forte, Rui Miguel. Mastering Predictive Analytics with R: Master the Craft of Predictive Modeling by Developing Strategy, Intuition, and a Solid Foundation in Essential Concepts. Packt Publishing, Limited, 2015.

Milman, Ruth. Speedup for the quadratic programming problem and other issues in model predictive control. 2004.

Indurkhya, Nitin, Tong Zhang y Sholom M. Weiss. Fundamentals of Predictive Text Mining. Springer London, Limited, 2015.

Fundamentals of Predictive Text Mining. Springer, 2012.

Indurkhya, Nitin, Tong Zhang y Sholom M. Weiss. Fundamentals of Predictive Text Mining. Springer, 2015.

Indurkhya, Nitin, Tong Zhang y Sholom M. Weiss. Fundamentals of Predictive Text Mining. Springer, 2010.

Stikman, Gene. ZOMBIE LIFE : the Sleeping Woke: Attack on Freedom with Predictive Programming and Cultural Revolution. Independently Published, 2022.

Machine Learning with R: Expert Techniques for Predictive Modeling, 3rd Edition. Packt Publishing, Limited, 2019.

Python for Beginners: The Absolute Beginners Guide to Python Programming, Data Science and Predictive Model. a Practical Introduction to Object Oriented Programming Language. Independently Published, 2019.

Machine Learning with R: Expert techniques for predictive modeling to solve all your data analysis. 2^a ed. Birmingham: Packt Publishing, 2015.

Machine Learning with R: Expert techniques for predictive modeling to solve all your data analysis problems, 2nd Edition. Packt Publishing, 2015.

Learning, Josh Hugh. Python for Beginners: A Step by Step Guide to Python Programming, Data Science, and Predictive Model. a Practical Introduction to Machine Learning with Python. Independently Published, 2019.

Mastering Machine Learning with Python in Six Steps: A Practical Implementation Guide to Predictive Data Analytics Using Python. Apress, 2017.

Georgiadis, Michael C., Vivek Dua y Efstratios N. Pistikopoulos. Multi-Parametric Model-Based Control: Theory and Applications. Wiley & Sons, Limited, John, 2011.

Process Systems Engineering: Volume 2: Multi-Parametric Model-Based Control (Process Systems Engineering). Wiley-VCH, 2007.

Georgiadis, Michael C., Vivek Dua y Efstratios N. Pistikopoulos. Multi-Parametric Model-Based Control: Theory and Applications. Wiley & Sons, Incorporated, John, 2021.

Multi-parametric model-based control. Weinheim: Wiley-VCH, 2006.

John, Russel. Data Science : 2 Books in 1: Python Programming & Python for Data Science, the Ultimate Guide to Learn Machine Learning and Predictive Analytics from Scratch with Hands-On Projects. Independently Published, 2019.

Clement, Mark J. Analytical performance prediction of data-parallel programs. 1994.

Microcomputer software for predicting growth of Southern timber stands. New Orleans, La: U.S. Dept. of Agriculture, Forest Service, Southern Forest Experiment Station, 1992.

Mastering Machine Learning with R: Advanced prediction, algorithms, and learning methods with R 3.x, 2nd Edition. Packt Publishing, 2017.

Shin, Frances B. y David H. Kil. Pattern Recognition and Prediction with Applications to Signal Processing (Modern Acoustics and Signal Processing). American Institute of Physics, 1998.

Girod, Bernd y Thomas Wiegand. Multi Frame Motion-Compensated Prediction for Video Transmission (The Springer International Series in Engineering and Computer Science). Springer, 2001.