Born at Purandar fort,he was raised by his paternal grandmother Jijabai. Shivaji signed the Treaty of Purandar with the Mughals, and sent Sambhaji to live with Raja Jai Singh of Amber, as a political hostage. Sambhaji was raised as a Mughal sardarand served the Mughal court of Aurangzeb. After Shivaji`s death, Sambhaji fought against his stepmother, Soyarabai Mohite, who had her son Rajaram crowned as the heir to the Maratha kingdom. Sambhaji escaped prison and formally ascended the throne on 20 July 1680. A brilliant tactician, Sambhaji was worthy of the throne of the Marathas, although his rule was short-lived. This book reveals his life story and showcases him for the ruler that he was.

    But in spirit, the title is apt, as the book does cover a much broader range of topics than a typical introductory book on mathematical statistics. This book is for people who want to learn probability and statistics quickly. It is suitable for graduate or advanced undergraduate students in computer science, mathematics, statistics, and related disciplines. The book includes modern topics like nonparametric curve estimation, bootstrapping, and clas- sification, topics that are usually relegated to follow-up courses. The reader is presumed to know calculus and a little linear algebra. No previous knowledge of probability and statistics is required. Statistics, data mining, and machine learning are all concerned with collecting and analyzing data. For some time, statistics research was con- ducted in statistics departments while data mining and machine learning re- search was conducted in computer science departments. Statisticians thought that computer scientists were reinventing the wheel. Computer scientists thought that statistical theory didn't apply to their problems. Things are changing. Statisticians now recognize that computer scientists are making novel contributions while computer scientists now recognize the generality of statistical theory and methodology. Clever data mining algo- rithms are more scalable than statisticians ever thought possible. Formal sta- tistical theory is more pervasive than computer scientists had realized.

    In the four main sections of the book, Stein tells the stories of the mathematical thinkers who discerned some of the most fundamental aspects of our universe. From their successes and failures, delusions, and even duels, the trajectories of their innovations—and their impact on society—are traced in this fascinating narrative. Quantum mechanics, space-time, chaos theory and the workings of complex systems, and the impossibility of a "perfect" democracy are all here. Stein's book is both mind-bending and practical, as he explains the best way for a salesman to plan a trip, examines why any thought you could have is imbedded in the number π , and—perhaps most importantly—answers one of the modern world's toughest questions: why the garage can never get your car repaired on time.Friendly, entertaining, and fun, How Math Explains the World is the first book by one of California's most popular math teachers, a veteran of both "math for poets" and Princeton's Institute for Advanced Studies. And it's perfect for any reader wanting to know how math makes both science and the world tick.

    The framework of probabilistic graphical models, presented in this book, provides a general approach for this task. The approach is model-based, allowing interpretable models to be constructed and then manipulated by reasoning algorithms. These models can also be learned automatically from data, allowing the approach to be used in cases where manually constructing a model is difficult or even impossible. Because uncertainty is an inescapable aspect of most real-world applications, the book focuses on probabilistic models, which make the uncertainty explicit and provide models that are more faithful to reality.Probabilistic Graphical Models discusses a variety of models, spanning Bayesian networks, undirected Markov networks, discrete and continuous models, and extensions to deal with dynamical systems and relational data. For each class of models, the text describes the three fundamental cornerstones: representation, inference, and learning, presenting both basic concepts and advanced techniques. Finally, the book considers the use of the proposed framework for causal reasoning and decision making under uncertainty. The main text in each chapter provides the detailed technical development of the key ideas. Most chapters also include boxes with additional material: skill boxes, which describe techniques; case study boxes, which discuss empirical cases related to the approach described in the text, including applications in computer vision, robotics, natural language understanding, and computational biology; and concept boxes, which present significant concepts drawn from the material in the chapter. Instructors (and readers) can group chapters in various combinations, from core topics to more technically advanced material, to suit their particular needs.

    Whether you're a student or retired, at the gym or at work, at the school gate or in the supermarket, here is a fresh and original framework for fruitfulness which will open up a host of possibilities to make a difference for Christ among the people you naturally meet in the places you find yourself day by day.Brimming with true stories, the combination of fresh Biblical insight, humour and practical steps will not only spark your imagination; it will enrich your sense of wonder at the greatness and grace of the God who not only gave his life for us, but invites us to join him in his glorious, transforming work.

    The book documents his incredible journey of Indian Cricket as he takes us inside dressing rooms, hotels and the inner thoughts of leading cricketers. With a foreword by Sachin Tendulkar, this book is laced with crackling humour and brimming with interesting anecdotes, insights, quotes, and candid photographs, from cricketing legends like Sachin Tendulkar, Rahul Dravid, Yuvraj Singh, Virender Sehwag, among others. This book promises to reveal many more inside secrets!

    I believe this is a function of the vector that the documentary photographer must have, to show one person's existence to another."—Sebastião SalgadoIllustrated with a compelling image from each photographer, Witness in Our Time traces the recent history of social documentary photography in the words of twenty-two of the genre's best photographers, editors, and curators, showing that the profession remains vital, innovative, and committed to social change. Featuring interviews with Hansel Mieth, Walter Rosenblum, Michelle Vignes, Wayne Miller, Peter Magubane, Matt Herron, Jill Freedman, Mary Ellen Mark, Earl Dotter, Eugene Richards, Susan Meiselas, Sebastião Salgado, Graciela Iturbide, Antonin Kratochvil, Donna Ferrato, Joseph Rodriguez, Dayanita Singh, Fazal Sheikh, Gifford Hampshire, Peter Howe, Colin Jacobson, and Ann Wilkes Tucker.Introduction: Seeing and believing / Kerry Tremain --Hansel Mieth: the depression and the early days of Life --Walter Rosenblum: Lewis Hine, Paul Strand, and the Photo League --Michelle Vignes: Magnum Photo Agency : the early years --Wayne Miller: World War II and the family of man --Peter Magubane: a black photographer in Apartheid South Africa --Matt Herron: the Civil Rights movement and the Southern documentary project --Jill Freedman: Resurrection City --Mary Ellen Mark: streetwise photographer --Earl Dotter: the United Mine Workers --Eugene Richards: Americans we --Susan Meiselas: Central America and human rights --Sebastião Salgado: workers --Graciela Iturbide: the indigenous of Mexico --Antonin Kratochvil: the fall of the Iron Curtain --Donna Ferrato: living with the enemy : domestic violence --Joseph Rodriguez: in the barrio --Dayanita Singh: a truer India --Fazal Sheikh: portrait of a refugee --Gifford Hampshire: the Environmental Protection Agency's Project DOCUMERICA --Peter Howe: Life magazine and Outtakes --Colin Jacobson: Independent magazine and Reportage --Anne Wilkes Tucker: the museum context --Fred Ritchin: the fish are last to know about the water: the emerging digital revolution --Rondal Partridge: Dorothea Lange in the field --Don McCullin: Vietnam : the Battle of Hue, 1968 --Bill Owens: Suburbia and a passion for seeing his world --Larry Fink: Social graces --David Goldblatt: once an enemy : Apartheid and the New South Africa --Maya Goded: Tierra Negra --Afterword: Witness in our time / Ken Light

    

    This book leads the reader from simple graphs through planar graphs, Euler's formula, Platonic graphs, coloring, the genus of a graph, Euler walks, Hamilton walks, more. Includes exercises. 1976 edition.

    This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience, R for Data Science is designed to get you doing data science as quickly as possible. Authors Hadley Wickham and Garrett Grolemund guide you through the steps of importing, wrangling, exploring, and modeling your data and communicating the results. You’ll get a complete, big-picture understanding of the data science cycle, along with basic tools you need to manage the details. Each section of the book is paired with exercises to help you practice what you’ve learned along the way. You’ll learn how to: Wrangle—transform your datasets into a form convenient for analysis Program—learn powerful R tools for solving data problems with greater clarity and ease Explore—examine your data, generate hypotheses, and quickly test them Model—provide a low-dimensional summary that captures true "signals" in your dataset Communicate—learn R Markdown for integrating prose, code, and results

    These two highly-respected economists and educators have revised this best-selling MICRO FIRST book to include more current topics and events while maintaining its hallmark feature of teaching economics through stories, graphs, and equations; relevant to students with various learning styles (verbal, visual, and numerical).

    Part I introduces concepts of thermodynamics and statistical mechanics from a unified view. Parts II and III explore further applications of classical thermodynamics and statistical mechanics. Throughout, the emphasis is on real-world applications.

    Now with the second edition, readers will find information on key new topics such as neural networks and statistical pattern recognition, the theory of machine learning, and the theory of invariances. Also included are worked examples, comparisons between different methods, extensive graphics, expanded exercises and computer project topics.An Instructor's Manual presenting detailed solutions to all the problems in the book is available from the Wiley editorial department.

    Now, Fundamental Analysis For Dummies puts this tried and true method for gauging any company's true underlying value into sensible and handy step-by-step instructions..In this easy-to-understand, practical, and savvy guide you'll discover why this powerful tool is particularly important to investors in times of economic downturn and how it helps you assess a business's overall financial performance by using historical and present data to forecast its future monetary value. You'll also learn how to use fundamental analysis to spot bargains in the market, minimize your risk, and improve your overall investment skills.Shows how to predict the future value of a business based on its current and historical financial data Helps you guage a company's performance against its competitors Covers evaluation of internal management Reveals how to determine if in a company's credit standing is any jeopardy Applies fundamental analysis to other investment vehicles, including currency, bonds, and commodities Matt Krantz is a writer and reporter for USA TODAY and USATODAY.COM where he covers investments and financial markets Read Fundamental Analysis For Dummies and find the bargains that could make you the next Warren Buffett!