Author: Dr T.K.V. Iyengar & Dr B. Krishna Gandhi & S. Ranganadham &
Dr M.V.S.S.N. PrasadPublisher: S. Chand Publishing
ISBN: 9352837487
Category : Science
Languages : en
Pages : 728
Book Description
Probability and Statistics & Complex Variables
Probability and Statistics & Complex Variables
Author: Dr T.K.V. Iyengar & Dr B. Krishna Gandhi & S. Ranganadham &
Dr M.V.S.S.N. PrasadPublisher: S. Chand Publishing
ISBN: 9352837487
Category : Science
Languages : en
Pages : 728
Book Description
Probability and Statistics & Complex Variables
PROBABILITY AND STATISTICS (HYDERABAD).
Author: T.K.V. IYENGARPublisher:
ISBN: 9789385401978
Category :
Languages : en
Pages :
Book Description
Probability and Statistics
Author: Dr T.K.V. Iyengar & Dr B. Krishna Gandhi & S. Ranganadham &
Dr M.V.S.S.N. PrasadPublisher: S. Chand Publishing
ISBN: 9352838270
Category : Science
Languages : en
Pages : 592
Book Description
This book comprises previous question papers problems at appropriate places and also previous GATE questions at the end of each chapter for the benefit of the students
A First Course in Probability and Statistics
Author: B. L. S. Prakasa RaoPublisher: World Scientific
ISBN: 9812836535
Category : Mathematics
Languages : en
Pages : 330
Book Description
This book provides a clear exposition of the theory of probability along with applications in statistics.
Probability,Statistics and Random Processes
Author: Pappu KousalyaPublisher: Pearson Education India
ISBN: 9332514143
Category : Statistics
Languages : en
Pages : 593
Book Description
Probability, Statistics and Random Processes is designed to meet the requirements of students and is intended for beginners to help them understand the concepts from the first principles. Spread across 16 chapters, it discusses the theoretical aspects that have been refined and updated to reflect the current developments in the subjects. It expounds on theoretical concepts that have immense practical applications, giving adequate proofs to establish significant theorems.
Engineering Mathematics Volume - III (Statistical and Numerical Methods) (For 1st Year - 2nd Semester of JNTU, Hyderabad)
Author: Iyenger T.K.V./ Gandhi, Krishna B./ Ranganatham S. & Prasad M.V.S.S.N.Publisher: S. Chand Publishing
ISBN: 9352832442
Category : Mathematics
Languages : en
Pages : 693
Book Description
Engineering Mathematics
High-Dimensional Probability
Author: Roman VershyninPublisher: Cambridge University Press
ISBN: 1108415199
Category : Business & Economics
Languages : en
Pages : 299
Book Description
An integrated package of powerful probabilistic tools and key applications in modern mathematical data science.
Computational Statistics with R
Author: Publisher: Elsevier
ISBN: 044463441X
Category : Mathematics
Languages : en
Pages : 413
Book Description
R is open source statistical computing software. Since the R core group was formed in 1997, R has been extended by a very large number of packages with extensive documentation along with examples freely available on the internet. It offers a large number of statistical and numerical methods and graphical tools and visualization of extraordinarily high quality. R was recently ranked in 14th place by the Transparent Language Popularity Index and 6th as a scripting language, after PHP, Python, and Perl. The book is designed so that it can be used right away by novices while appealing to experienced users as well. Each article begins with a data example that can be downloaded directly from the R website. Data analysis questions are articulated following the presentation of the data. The necessary R commands are spelled out and executed and the output is presented and discussed. Other examples of data sets with a different flavor and different set of commands but following the theme of the article are presented as well. Each chapter predents a hands-on-experience. R has superb graphical outlays and the book brings out the essentials in this arena. The end user can benefit immensely by applying the graphics to enhance research findings. The core statistical methodologies such as regression, survival analysis, and discrete data are all covered. - Addresses data examples that can be downloaded directly from the R website - No other source is needed to gain practical experience - Focus on the essentials in graphical outlays
Perspectives In Mathematical Science I: Probability And Statistics
Author: N S Narasimha SastryPublisher: World Scientific
ISBN: 9814467863
Category : Mathematics
Languages : en
Pages : 283
Book Description
This book presents a collection of invited articles by distinguished probabilists and statisticians on the occasion of the Platinum Jubilee Celebrations of the Indian Statistical Institute — a notable institute with significant achievement in research areas of statistics, probability and mathematics — in 2007.With a wide coverage of topics in probability and statistics, the articles provide a current perspective of different areas of research, emphasizing the major challenging issues. The book also proves its reference and utility value for practitioners as the articles in Statistics contain applications of the methodology that will be of use to practitioners. To professional statisticians and mathematicians, this is a unique volume for its illuminating perspectives on several important aspects of probability and statistics.
Machine Learning and Big Data
Author: Uma N. DulharePublisher: John Wiley & Sons
ISBN: 1119654742
Category : Computers
Languages : en
Pages : 544
Book Description
This book is intended for academic and industrial developers, exploring and developing applications in the area of big data and machine learning, including those that are solving technology requirements, evaluation of methodology advances and algorithm demonstrations. The intent of this book is to provide awareness of algorithms used for machine learning and big data in the academic and professional community. The 17 chapters are divided into 5 sections: Theoretical Fundamentals; Big Data and Pattern Recognition; Machine Learning: Algorithms & Applications; Machine Learning's Next Frontier and Hands-On and Case Study. While it dwells on the foundations of machine learning and big data as a part of analytics, it also focuses on contemporary topics for research and development. In this regard, the book covers machine learning algorithms and their modern applications in developing automated systems. Subjects covered in detail include: Mathematical foundations of machine learning with various examples. An empirical study of supervised learning algorithms like Naïve Bayes, KNN and semi-supervised learning algorithms viz. S3VM, Graph-Based, Multiview. Precise study on unsupervised learning algorithms like GMM, K-mean clustering, Dritchlet process mixture model, X-means and Reinforcement learning algorithm with Q learning, R learning, TD learning, SARSA Learning, and so forth. Hands-on machine leaning open source tools viz. Apache Mahout, H2O. Case studies for readers to analyze the prescribed cases and present their solutions or interpretations with intrusion detection in MANETS using machine learning. Showcase on novel user-cases: Implications of Electronic Governance as well as Pragmatic Study of BD/ML technologies for agriculture, healthcare, social media, industry, banking, insurance and so on.