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Multiple View Geometry in Computer Vision
Richard Hartley - 2000
This book covers relevant geometric principles and how to represent objects algebraically so they can be computed and applied. Recent major developments in the theory and practice of scene reconstruction are described in detail in a unified framework. Richard Hartley and Andrew Zisserman provide comprehensive background material and explain how to apply the methods and implement the algorithms. First Edition HB (2000): 0-521-62304-9
A Course of Pure Mathematics
G.H. Hardy - 1908
Since its publication in 1908, it has been a classic work to which successive generations of budding mathematicians have turned at the beginning of their undergraduate courses. In its pages, Hardy combines the enthusiasm of a missionary with the rigor of a purist in his exposition of the fundamental ideas of the differential and integral calculus, of the properties of infinite series and of other topics involving the notion of limit.
Linear Systems and Signals
B.P. Lathi - 1992
It gives clear descriptions of linear systems and uses mathematics not only to prove axiomatic theory, but also to enhance physical and intuitive understanding.
Topology
James R. Munkres - 1975
Includes many examples and figures. GENERAL TOPOLOGY. Set Theory and Logic. Topological Spaces and Continuous Functions. Connectedness and Compactness. Countability and Separation Axioms. The Tychonoff Theorem. Metrization Theorems and paracompactness. Complete Metric Spaces and Function Spaces. Baire Spaces and Dimension Theory. ALGEBRAIC TOPOLOGY. The Fundamental Group. Separation Theorems. The Seifert-van Kampen Theorem. Classification of Surfaces. Classification of Covering Spaces. Applications to Group Theory. For anyone needing a basic, thorough, introduction to general and algebraic topology and its applications.
Introduction to Graph Theory
Douglas B. West - 1995
Verification that algorithms work is emphasized more than their complexity. An effective use of examples, and huge number of interesting exercises, demonstrate the topics of trees and distance, matchings and factors, connectivity and paths, graph coloring, edges and cycles, and planar graphs. For those who need to learn to make coherent arguments in the fields of mathematics and computer science.
No Nonsense Real Estate: What Everyone Should Know Before Buying or Selling a Home
Alex Goldstein - 2016
straight from an experienced pro that has seen millions of dollars exchange hands at the closing table.” - Peter Voogd, #1 International Bestselling Author of 6 Months to 6 Figures There are countless real estate books on the market today, so why read this one? What sets it apart from all the others out there?Bestselling Author, Alex Goldstein, brings a unique perspective that many others do not. As a successful realtor and investor, Alex has been on both sides of a real estate transaction, so he knows what strategies and techniques will lead to a successful deal, and which ones should be avoided at all costs. That’s why he chose the name, "No Nonsense Real Estate," for his third book.Goldstein offers practical, proven home buying techniques, free of fluff or confusing jargon.This book is for anyone who is getting ready to buy or sell a home and wants to be as informed as possible as they get ready to begin the process so there are no surprises – whether they will be working with a realtor or doing it on their own.
9 REASONS TO READ THIS BOOK NOW:
1. AGENT - Go through the pros and cons of working with a real estate agent, and the two ways that they can add the most value,2. ECONOMICS - You'll understand the fundamental economics of the housing market in the simplest terms possible3. INVESTING - Avoid the top five mistakes (almost) all new real estate investors make4. NEGOTIATIONS - Five critical elements of a successful negotiation5. FINANCING - Possible financing options, from traditional loans to seller financing6. SELLING - Seven secrets that make selling a home as painless as possible7. BUYING - Demystifying contracts and closing costs takes the fear out of the process8. CLOSING - Walk through eight steps involved in a real estate transaction closing9. PRACTICAL - Learn how all the different parts come together in a real life case studyYou also receive three free gifts. Goldstein has put together a special document answering the most popular questions every buyer, seller or investor has during a real estate transaction. You also get special access to an easy-to-understand glossary of the most popular real estate jargon. Last but not least, every reader is access to a free video training that will teach you how to choose the best home for your family.
Essential Elements for Strings: Book 1 with CD-ROM (Violin)
Michael Allen - 2002
Introducing Hal Leonard's Essential Elements 2000 for Strings Plus DVD. Instrumentation - Violin
Hands-On Machine Learning with Scikit-Learn and TensorFlow
Aurélien Géron - 2017
Now that machine learning is thriving, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This practical book shows you how.By using concrete examples, minimal theory, and two production-ready Python frameworks—Scikit-Learn and TensorFlow—author Aurélien Géron helps you gain an intuitive understanding of the concepts and tools for building intelligent systems. You’ll learn how to use a range of techniques, starting with simple Linear Regression and progressing to Deep Neural Networks. If you have some programming experience and you’re ready to code a machine learning project, this guide is for you.This hands-on book shows you how to use:Scikit-Learn, an accessible framework that implements many algorithms efficiently and serves as a great machine learning entry pointTensorFlow, a more complex library for distributed numerical computation, ideal for training and running very large neural networksPractical code examples that you can apply without learning excessive machine learning theory or algorithm details
Introductory Statistics with R
Peter Dalgaard - 2002
It can be freely downloaded and it works on multiple computer platforms. This book provides an elementary introduction to R. In each chapter, brief introductory sections are followed by code examples and comments from the computational and statistical viewpoint. A supplementary R package containing the datasets can be downloaded from the web.
Think Stats
Allen B. Downey - 2011
This concise introduction shows you how to perform statistical analysis computationally, rather than mathematically, with programs written in Python.You'll work with a case study throughout the book to help you learn the entire data analysis process—from collecting data and generating statistics to identifying patterns and testing hypotheses. Along the way, you'll become familiar with distributions, the rules of probability, visualization, and many other tools and concepts.Develop your understanding of probability and statistics by writing and testing codeRun experiments to test statistical behavior, such as generating samples from several distributionsUse simulations to understand concepts that are hard to grasp mathematicallyLearn topics not usually covered in an introductory course, such as Bayesian estimationImport data from almost any source using Python, rather than be limited to data that has been cleaned and formatted for statistics toolsUse statistical inference to answer questions about real-world data
Operations Research: An Introduction
Hamdy A. Taha - 1976
The applications and computations in operations research are emphasized. Significantly revised, this text streamlines the coverage of the theory, applications, and computations of operations research. Numerical examples are effectively used to explain complex mathematical concepts. A separate chapter of fully analyzed applications aptly demonstrates the diverse use of OR. The popular commercial and tutorial software AMPL, Excel, Excel Solver, and Tora are used throughout the book to solve practical problems and to test theoretical concepts. New materials include Markov chains, TSP heuristics, new LP models, and a totally new simplex-based approach to LP sensitivity analysis.
Challenge And Thrill Of Pre College Mathematics
V. Krishnamurthy - 2009
It can urge the reader to explore new methodologies to have maximum fun with numbers, and opt for a higher course in mathematics. The book was specifically designed to help the student community, and develop a strong affinity towards problem solving.the book offers many complicated, and interesting challenges for the user, keeping them engaged throughout. A large number of solved problems are also included in challenge and thrill of pre-college mathematics, to give readers an insight into the subject. The book can be an eye-opener for school students of class 7 and above. The materials given in the book are powerful enough to help them develop a strong interest for the subject. The concepts are explained in a simple and comprehensive manner, providing them with a good understanding of mathematical fundamentals.what makes the book distinct is its detailed sections on geometry, that can improve the reasoning skills of students. There are also detailed accounts on algebra and trigonometry, enhancing the competitive ability of the users. The topics such as combinatorics, number theory, and probability are also explained in detail, in the book. Each chapter was designed with the intention of motivating students to appreciate the excitement that mathematical problems can provide. Published in 2003 by new age international publishers, the book is available in paperback. Key features: the book includes a collection of more than 300 solved numerical problems, compiled from various national, as well as international mathematical olympiads.it is widely recommended by students and teachers, alike as an essential preparatory book for those writing competitive examinations.
Proofs and Refutations: The Logic of Mathematical Discovery
Imre Lakatos - 1976
Much of the book takes the form of a discussion between a teacher and his students. They propose various solutions to some mathematical problems and investigate the strengths and weaknesses of these solutions. Their discussion (which mirrors certain real developments in the history of mathematics) raises some philosophical problems and some problems about the nature of mathematical discovery or creativity. Imre Lakatos is concerned throughout to combat the classical picture of mathematical development as a steady accumulation of established truths. He shows that mathematics grows instead through a richer, more dramatic process of the successive improvement of creative hypotheses by attempts to 'prove' them and by criticism of these attempts: the logic of proofs and refutations.