JNTUA B.TECH R 20 2-3 Syllabus For Deterministic &stochasticstatistical methods PDF 2022


JNTUA B.TECH R 20 2-3 Syllabus For Deterministic &stochasticstatistical methods PDF 2022

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You will be able to find information about Deterministic &stochasticstatistical methods along with its Course Objectives and Course outcomes and also a list of textbook and reference books in this blog.You will get to learn a lot of new stuff and resolve a lot of questions you may have regarding Deterministic &stochasticstatistical methods after reading this blog. Deterministic &stochasticstatistical methods has 5 units altogether and you will be able to find notes for every unit on the CynoHub app. Deterministic &stochasticstatistical methods can be learnt easily as long as you have a well planned study schedule and practice all the previous question papers, which are also available on the CynoHub app.

All of the Topic and subtopics related to Deterministic &stochasticstatistical methods are mentioned below in detail. If you are having a hard time understanding Deterministic &stochasticstatistical methods or any other Engineering Subject of any semester or year then please watch the video lectures on the official CynoHub app as it has detailed explanations of each and every topic making your engineering experience easy and fun.

Deterministic &stochasticstatistical methods Unit One

Data Representation

Distance measures, Projections, Notion of hyper planes, half-planes. Principal Component Analysis-Population Principal Components, sample principal coefficients, covariance, matrix of data set, Dimensionality reduction, Singular value decomposition, Gram Schmidt process.

Deterministic &stochasticstatistical methods Unit Two

Single Variable Distribution

Random variables (discrete and continuous), probability density functions, properties, mathematical expectation-Probability distribution -Binomial, Poisson approximation to the binomial distribution and normal distribution-their properties-Uniform distribution-exponential distribution.

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Deterministic &stochasticstatistical methods Unit Three

Stochastic Processes And Markov Chains:

Introduction to Stochastic processes-Markov process. Transition Probability, Transition Probability Matrix, First order and Higher order Markov process, step transition probabilities, Markov chain, Steady state condition, Markov analysis.

Deterministic &stochasticstatistical methods Unit Four

Multivariate Distribution Theory

Multivariate Normal distribution –Properties, Distributions of linear combinations, independence, marginal distributions, conditional distributions, Partial and Multiple correlation coefficient. Moment generating function.BAYESIAN INFERENCE AND ITS APPLICATIONS: Statisticaltests and Bayesian model comparison, Bit, Surprisal,Entropy, Source coding theorem, Joint entropy, Conditional entropy, Kullback-Leibler divergence.

Deterministic &stochasticstatistical methods Unit Five


Unconstrained optimization, Necessary and sufficiency conditions for optima,Gradient descent methods, Constrained optimization, KKT conditions, Introduction to non-gradient techniques, Introduction to least squares optimization, Optimization view of machine learning. Data Science Methods: Linear regression as an exemplar functionapproximation problem, linear classification problems.

Deterministic &stochasticstatistical methods Course Objectives

This course provides a study of various Mathematical Methods and Statistical Methods which is needed for Artificial Intelligence, Machine Learning, and Data Science and also for Computer Science and engineering problems.

Deterministic &stochasticstatistical methods Course Outcomes

After completion of the course, students will be able to•Apply logical thinking to problem-solving in context.•Employ methods related to these concepts in a variety of data science applications.•Use appropriate technology to aid problem-solving and data analysis.•The Bayesian process of inference in probabilistic reasoning system.•Demonstrate skills in unconstrained optimization.

Deterministic &stochasticstatistical methods Text Books

1.Mathematics for Machine Learning by A. Aldo Faisal, Cheng Soon Ong, and Marc Peter Deisenroth2.Dr.B.S Grewal, Higher Engineering Mathematics, 45th Edition, Khanna Publishers. 3.Operations Research, S.D. Sharma

Deterministic &stochasticstatistical methods Reference Books

1.Operations Research, An Introduction, Hamdy A. Taha, Pearson publishers.2.A Probabilistic Theory of Pattern Recognition by Luc Devroye,. Laszlo Gyorfi, Gabor Lugosi.

Scoring Marks in Deterministic &stochasticstatistical methods

Scoring a really good grade in Deterministic &stochasticstatistical methods is a difficult task indeed and CynoHub is here to help!. Please watch the video below and find out how to get 1st rank in your examinations . This video will also inform students on how to score high grades in Deterministic &stochasticstatistical methods. There are a lot of reasons for getting a bad score in your Deterministic &stochasticstatistical methods exam and this video will help you rectify your mistakes and help you improve your grades.

Information about JNTUA B.Tech R 20 Deterministic &stochasticstatistical methods was provided in detail in this article. To know more about the syllabus of other Engineering Subjects of JNTUH check out the official CynoHub application. Click below to download the CynoHub application.

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