The series is a comprehensive package containing chapter wise and topic wise guidelines with a vast variety of solved and unsolved exercises to help students practice what they have learnt. These books are strictly in accordance with the latest CBSE syllabus and covers all aspects of formative and summative assessments with the latest marking schemes as laid down by CBSE.
The series is a comprehensive package containing chapter wise and topic wise guidelines with a vast variety of solved and unsolved exercises to help students practice what they have learnt. These books are strictly in accordance with the latest CBSE syllabus and covers all aspects of formative and summative assessments with the latest marking schemes as laid down by CBSE.
The series is a comprehensive package containing chapter wise and topic wise guidelines with a vast variety of solved and unsolved exercises to help students practice what they have learnt. These books are strictly in accordance with the latest CBSE syllabus and covers all aspects of formative and summative assessments with the latest marking schemes as laid down by CBSE.
The series is a comprehensive package containing chapter wise and topic wise guidelines with a vast variety of solved and unsolved exercises to help students practice what they have learnt. These books are strictly in accordance with the latest CBSE syllabus and covers all aspects of formative and summative assessments with the latest marking schemes as laid down by CBSE.
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.
In the early twentieth century, a massive undertaking to rid mathematics of all paradoxes and inconsistencies was underway. Known as Hilbert's program, it sought to provide an unshakable foundation for all of mathematics. Things seemed to be proceeding well until young Kurt Godel stunned the world by proving that Hilbert's goals were unobtainable, that contradiction was part of the warp and weave of any mathematical system. Yet what at the time seemed to be a fatal blow to mathematical consistency now forms the basis of modern logic. Godel's incompleteness theorems are often misunderstood to be a statement of the limits of mathematical reasoning, but in truth they strengthen mathematics, building it up to be more powerful than what had come before. In this third book in the Math Girls series, join Miruka and friends as they tackle the basics of modern logic, learning such topics as the Peano axioms, set theory, and diagonalization, leading up to an in-depth exploration of Godel's famous theorems. Along the way, visit other interesting and important topics such as trigonometry and the epsilon-delta definition of limits, and of course take on challenges from the enigmatic Mr. Muraki. Math Girls 3: Godel's Incompleteness Theorems has something for anyone interested in mathematics, from advanced high school students to college math majors and educators."
An awesome, globe-spanning, and New York Times bestselling journey through the beauty and power of mathematics What if you had to take an art class in which you were only taught how to paint a fence? What if you were never shown the paintings of van Gogh and Picasso, weren't even told they existed? Alas, this is how math is taught, and so for most of us it becomes the intellectual equivalent of watching paint dry. In Love and Math, renowned mathematician Edward Frenkel reveals a side of math we've never seen, suffused with all the beauty and elegance of a work of art. In this heartfelt and passionate book, Frenkel shows that mathematics, far from occupying a specialist niche, goes to the heart of all matter, uniting us across cultures, time, and space. Love and Math tells two intertwined stories: of the wonders of mathematics and of one young man's journey learning and living it. Having braved a discriminatory educational system to become one of the twenty-first century's leading mathematicians, Frenkel now works on one of the biggest ideas to come out of math in the last 50 years: the Langlands Program. Considered by many to be a Grand Unified Theory of mathematics, the Langlands Program enables researchers to translate findings from one field to another so that they can solve problems, such as Fermat's last theorem, that had seemed intractable before. At its core, Love and Math is a story about accessing a new way of thinking, which can enrich our lives and empower us to better understand the world and our place in it. It is an invitation to discover the magic hidden universe of mathematics.
In this book an experienced classroom teacher and noted researcher on teaching takes us into her fifth grade math class through the course of a year. Magdalene Lampert shows how classroom dynamics--the complex relationship of teacher, student, and content--are critical in the process of bringing each student to a deeper understanding of mathematics, or any other subject. She offers valuable insights into students and teaching for all who are concerned about improving the learning that happens in the classroom. Lampert considers the teacher's and students' work from many different angles, in views large and small. She analyzes her own practice in a particular classroom, student by student and moment by moment. She also investigates the particular kind of teaching that aims at engaging elementary school students in learning fundamentally important ideas and skills by working on problems. Finally, she looks at the common problems of teaching that occur regardless of the individuals, subject matter, or kinds of practice involved. Lampert arrives at an original model of teaching practice that casts new light on the complexity in teachers' work and on the ways teachers can successfully deal with teaching problems.
There was a time when 'universe' meant all there is. Everything. Yet, as Brian Greene's extraordinary book shows, ours may be just one universe among many, like endless reflections in a mirror. He takes us on a captivating exploration of parallel worlds - from a multiverse where an infinite number of your doppelg ngers are reading this sentence, to vast oceans of bubble universes and even multiverses made of mathematics - showing just how much of reality's true nature may be hidden within them.
