Machine Learning, Artificial Intelligence, Mathematics eBooks

[emil2992]

Machine Learning, Artificial Intelligence, Mathematics eBooks

PDF | English | 1.22 GB

List:

artificial general intelligence (2007).pdf5.7 Mb
artificial intelligence (luger, 6th, 2008).pdf4.03 M
artificial intelligence - a modern approach (3rd, 2009).pdf14.85 Mb
artificial intelligence for games (2nd, 2009).pdf
a field guide to genetic programming (2008).pdf3.59 Mb
ant colony optimization (2004).pdf1.88 Mb
bio-inspired artificial intelligence (2008).pdf14.93 Mb
evolving connectionist systems - the knowledge engineering approach (2007).pdf16.63 Mb
introduction to evolutionary computing (2003).pdf44.95 Mb
swarm intelligence (2001).pdf9.02 Mb
the art of artificial evolution - a handbook on evolutionary art and music (2007).pdf
knowledge representation and reasoning (2004).pdf2.29 Mb
prediction, learning, and games (2006).pdf5.53 Mb
reinforcement learning - an introduction (1998).pdf4.04 Mb
the quest for AI - a history of ideas and achievements (2010).pdf15.32 Mb
universal artificial intelligence (2005).pdf
calculus (spivak, 3rd, 1994).pdf48.37 Mb
calculus (strang, 1991).pdf33.53 Mb
introduction to analysis (1985).pdf
fundamentals of matrix computations (2nd, 2002).pdf25.59 Mb
introduction to linear algebra (4th, 2009).pdf89.94 Mb
linear algebra (1977).djvu14.12 Mb
matrix algebra - theory, computations, and applications in statistics (2007).pdf3.83 Mb
matrix computations (3rd, 1996).pdf11.56 Mb
matrix cookbook.pdf522.2 Kb
convex optimization (2004).pdf6.32 Mb
introduction to linear optimization (1997).pdf13.54 Mb
introduction to stochastic search and optimization (2003).djvu5.22 Mb
numerical optimization (2nd, 2006).pdf3.25 Mb
optimization for machine learning (2011).pdf2.98 Mb
practical methods for optimization (2nd, 1987).pdf
a course in probability theory (3rd, 2000).pdf20.47 Mb
a first look at rigorous probability theory (2nd, 2006).pdf3.12 Mb
an introduction to probability theory and applications (vol1, 3rd, 1968).pdf35.11 Mb
an introduction to probability theory and applications (vol2, 1971).pdf42.09 Mb
introduction to probability (bertsekas, 2nd, 2008).pdf17.37 Mb
introduction to probability (grinstead and snell, 2006).pdf2.85 Mb
probability theory - the logic of science (2003).pdf5.81 Mb
schaum's outline of probability, random variables and random processes (1997).pdf
all of nonparametric statistics (2010).pdf2.18 Mb
all of statistics - a concise course in statistical inference (2010).pdf44.94 Mb
an introduction to generalized linear models (2nd, 2001).pdf2.07 Mb
applied linear statistical models (5th, 2004).pdf49.8 Mb
introduction to bayesian statistics (2nd, 2007).pdf21.85 Mb
modern multivariate statistical techniques - regression, classification and manifold learning (2008).pdf11.77 Mb
multivariate data analysis (7th, 2009).pdf11.11 Mb
robust statistics (2nd, 2009).pdf13.78 Mb
statistics - the exploration and analysis of data (7th, 2010).pdf12.15 Mb
statistics in plain english (3rd, 2010).pdf
a probabilistic theory of pattern recognition (1996).pdf10.78 Mb
an introduction to information retrieval (2009).pdf6.58 Mb
an introduction to pattern recognition - a matlab approach (2010).pdf3.35 Mb
bayesian reasoning and machine learning (2012).pdf13.58 Mb
data analysis with open source tools (2010).pdf10.16 Mb
data mining - concepts and techniques (3rd, 2011).pdf12.53 Mb
data mining - practical machine learning tools and techniques (2011).pdf6.94 Mb
doing bayesian data analysis - a tutorial with R and BUGS (2010).pdf9.91 Mb
elements of statistical learning (2008).pdf12.33 Mb
ensemble methods in data mining (2010).pdf2.6 Mb
gaussian processes for machine learning (2005).pdf3.86 Mb
information theory, inference and learning algorithms (2003).pdf7.06 Mb
introduction to machine learning (alpaydin, 2009).pdf3.52 Mb
introduction to machine learning (smola, 2010).pdf10.31 Mb
kernel methods for pattern analysis (2004).pdf3.02 Mb
large-scale inference - empirical bayes methods for estimation, testing, and prediction (2010).pdf3.63 Mb
learning deep architectures for AI (2009).pdf1.08 Mb
learning with kernels (2002).pdf9.81 Mb
machine learning (1997).pdf37 Mb
machine learning - an algorithmic perspective (2009).pdf41.92 Mb
machine learning for hackers (2012).pdf23.08 Mb
mining the social web - analyzing data from facebook, twitter, linkedin and other social media sites (2011).pdf4.81 Mb
neural networks for applied sciences and engineering (2006).pdf5.86 Mb
pattern recognition (4th, 2008).pdf13.23 Mb
pattern recognition and machine learning (2007).pdf4.52 Mb
probabilistic graphical models - principles and techniques (2009).pdf66.17 Mb
programming collective intelligence - building smart web 2.0 applications (2007).pdf3.3 Mb
statistical learning theory (1998).pdf

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