Laboratory Manual for Mathematics – 7

Laboratory Manual for Mathematics – 7
Author: Rajesh Singh
Publisher: Vikas Publishing House
Total Pages: 221
Release:
Genre: Mathematics
ISBN: 9325980231

An important dictum of learning is that theoretical learning must always be supplemented by practical learning. This ensures proper understanding and comprehension besides better retention. It eliminates the phobia and makes learning fun. With this in mind the concept of activities in mathematics was introduced. This series of books caters to the above requirement. It is a sincere effort to sharpen the intellect through activity oriented learning to acquire mathematical skills and develop logical reasoning. The ebook version does not contain CD.

Lab Math

Lab Math
Author: Dany Spencer Adams
Publisher: CSHL Press
Total Pages: 292
Release: 2003
Genre: Mathematics
ISBN: 9780879696344

Work at the biology bench requires an ever-increasing knowledge of mathematical methods and formulae. This is a compilation of the most common mathematical concepts and methods in molecular biology, with clear, straightforward guidance on their application to research investigations.

Composite Mathematics For Class 7

Composite Mathematics For Class 7
Author: ANUBHUTI GANGAL
Publisher: S. Chand Publishing
Total Pages: 358
Release:
Genre: Mathematics
ISBN: 9352831438

Composite Mathematics is a series of books for Pre Primer to Class 8 which conforms to the latest CBSE curriculum. The main aim of writing this series is to help the children understand difficult mathematical concepts in a simple manner in easy language.

Laboratory Manual of Biomathematics

Laboratory Manual of Biomathematics
Author: Raina Robeva
Publisher: Academic Press
Total Pages: 187
Release: 2007-08-28
Genre: Computers
ISBN: 0123740223

Laboratory Manual of Biomathematics is a companion to the textbook An Invitation to Biomathematics. This laboratory manual expertly aids students who wish to gain a deeper understanding of solving biological issues with computer programs. It provides hands-on exploration of model development, model validation, and model refinement, enabling students to truly experience advancements made in biology by mathematical models. Each of the projects offered can be used as individual module in traditional biology or mathematics courses such as calculus, ordinary differential equations, elementary probability, statistics, and genetics. Biological topics include: Ecology, Toxicology, Microbiology, Epidemiology, Genetics, Biostatistics, Physiology, Cell Biology, and Molecular Biology . Mathematical topics include Discrete and continuous dynamical systems, difference equations, differential equations, probability distributions, statistics, data transformation, risk function, statistics, approximate entropy, periodic components, and pulse-detection algorithms. It includes more than 120 exercises derived from ongoing research studies. This text is designed for courses in mathematical biology, undergraduate biology majors, as well as general mathematics. The reader is not expected to have any extensive background in either math or biology. Can be used as a computer lab component of a course in biomathematics or as homework projects for independent student work Biological topics include: Ecology, Toxicology, Microbiology, Epidemiology, Genetics, Biostatistics, Physiology, Cell Biology, and Molecular Biology Mathematical topics include: Discrete and continuous dynamical systems, difference equations, differential equations, probability distributions, statistics, data transformation, risk function, statistics, approximate entropy, periodic components, and pulse-detection algorithms Includes more than 120 exercises derived from ongoing research studies

LK-Mathematics-HB-10-R

LK-Mathematics-HB-10-R
Author: Anupal Sagar, Rashmi Sagar
Publisher: New Saraswati House India Pvt Ltd
Total Pages: 224
Release:
Genre: Mathematics
ISBN: 9352723791

LK-Mathematics-HB-10-R

Laboratory Manual for Mathematics – 9

Laboratory Manual for Mathematics – 9
Author: Rajesh Singh
Publisher: Vikas Publishing House
Total Pages: 193
Release:
Genre: Mathematics
ISBN: 9325980258

An important dictum of learning is that theoretical learning must always be supplemented by practical learning. This ensures proper understanding and comprehension besides better retention. It eliminates the phobia and makes learning fun. With this in mind the concept of activities in mathematics was introduced. This series of books caters to the above requirement. It is a sincere effort to sharpen the intellect through activity oriented learning to acquire mathematical skills and develop logical reasoning. The ebook version does not contain CD.

Laboratory Manual for Mathematics – 10

Laboratory Manual for Mathematics – 10
Author: Rajesh Singh
Publisher: Vikas Publishing House
Total Pages: 181
Release:
Genre: Mathematics
ISBN: 9325980266

An important dictum of learning is that theoretical learning must always be supplemented by practical learning. This ensures proper understanding and comprehension besides better retention. It eliminates the phobia and makes learning fun. With this in mind the concept of activities in mathematics was introduced. This series of books caters to the above requirement. It is a sincere effort to sharpen the intellect through activity oriented learning to acquire mathematical skills and develop logical reasoning. The ebook version does not contain CD.

Mathematics for Machine Learning

Mathematics for Machine Learning
Author: Marc Peter Deisenroth
Publisher: Cambridge University Press
Total Pages: 392
Release: 2020-04-23
Genre: Computers
ISBN: 1108569323

The fundamental mathematical tools needed to understand machine learning include linear algebra, analytic geometry, matrix decompositions, vector calculus, optimization, probability and statistics. These topics are traditionally taught in disparate courses, making it hard for data science or computer science students, or professionals, to efficiently learn the mathematics. This self-contained textbook bridges the gap between mathematical and machine learning texts, introducing the mathematical concepts with a minimum of prerequisites. It uses these concepts to derive four central machine learning methods: linear regression, principal component analysis, Gaussian mixture models and support vector machines. For students and others with a mathematical background, these derivations provide a starting point to machine learning texts. For those learning the mathematics for the first time, the methods help build intuition and practical experience with applying mathematical concepts. Every chapter includes worked examples and exercises to test understanding. Programming tutorials are offered on the book's web site.