Star Maths Class 4 Part A, Part B, Part C & Part D (Four Booklets)
Author: Dr. Anupriya Pandya
Publisher: Goyal Brothers Prakashan
Published: 2020-01-01
Total Pages: 334
ISBN-13: 9388676122
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Author: Dr. Anupriya Pandya
Publisher: Goyal Brothers Prakashan
Published: 2020-01-01
Total Pages: 334
ISBN-13: 9388676122
DOWNLOAD EBOOKGoyal Brothers Prakashan
Author: Dr. Anupriya Pandya
Publisher: Goyal Brothers Prakashan
Published: 2019-01-01
Total Pages: 288
ISBN-13: 9388676114
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Author: Dr. Anupriya Pandya
Publisher: Goyal Brothers Prakashan
Published: 2019-01-01
Total Pages: 400
ISBN-13: 9388676130
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Author: Dr. Anupriya Pandya
Publisher: Goyal Brothers Prakashan
Published: 2020-01-01
Total Pages:
ISBN-13: 9388676106
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DOWNLOAD EBOOKAuthor: Erika Warecki
Publisher: Learning Express (NY)
Published: 2002
Total Pages: 0
ISBN-13: 9781576854167
DOWNLOAD EBOOKGetting Ready for the 4th Grade Assessment Test: Help Improve Your Child’s Math and English Skills – Many parents are expressing a demand for books that will help their children succeed and excel on the fourth grade assessment tests in math and English –especially in areas where children have limited access to computers. This book will help students practice basic math concepts, i.e., number sense and applications as well as more difficult math, such as patterns, functions, and algebra. English skills will include practice in reading comprehension, writing, and vocabulary. Rubrics are included for self-evaluation.
Author: Marc Peter Deisenroth
Publisher: Cambridge University Press
Published: 2020-04-23
Total Pages: 392
ISBN-13: 1108569323
DOWNLOAD EBOOKThe 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.
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Published: 2011
Total Pages:
ISBN-13: 9780547404783
DOWNLOAD EBOOKAuthor: Colin Conrad Adams
Publisher: American Mathematical Soc.
Published: 2004
Total Pages: 330
ISBN-13: 0821836781
DOWNLOAD EBOOKKnots are familiar objects. Yet the mathematical theory of knots quickly leads to deep results in topology and geometry. This work offers an introduction to this theory, starting with our understanding of knots. It presents the applications of knot theory to modern chemistry, biology and physics.
Author: Tilman M. Davies
Publisher: No Starch Press
Published: 2016-07-16
Total Pages: 833
ISBN-13: 1593276516
DOWNLOAD EBOOKThe Book of R is a comprehensive, beginner-friendly guide to R, the world’s most popular programming language for statistical analysis. Even if you have no programming experience and little more than a grounding in the basics of mathematics, you’ll find everything you need to begin using R effectively for statistical analysis. You’ll start with the basics, like how to handle data and write simple programs, before moving on to more advanced topics, like producing statistical summaries of your data and performing statistical tests and modeling. You’ll even learn how to create impressive data visualizations with R’s basic graphics tools and contributed packages, like ggplot2 and ggvis, as well as interactive 3D visualizations using the rgl package. Dozens of hands-on exercises (with downloadable solutions) take you from theory to practice, as you learn: –The fundamentals of programming in R, including how to write data frames, create functions, and use variables, statements, and loops –Statistical concepts like exploratory data analysis, probabilities, hypothesis tests, and regression modeling, and how to execute them in R –How to access R’s thousands of functions, libraries, and data sets –How to draw valid and useful conclusions from your data –How to create publication-quality graphics of your results Combining detailed explanations with real-world examples and exercises, this book will provide you with a solid understanding of both statistics and the depth of R’s functionality. Make The Book of R your doorway into the growing world of data analysis.