The new edition features additional styles and functions, improved font handling, and enhanced graphics capabilities. Other parts of the book have been revised to reflect user comments and suggestions. Selected sections have been rewritten to explain challenging concepts or functions, and the descriptions of both MakeIndex and BibTEX have been updated. New LATEX users will want to start with this book, and current users, particularly as they upgrade to the LATEX2e software, will be eager to obtain the most up-to-date version of its associated manual. Features Revised version of the authoritative user's guide and reference manual for the LATEX computer typesetting system. Features the new standard software release - LATEX2e. Sections rewritten to explain difficult concepts or functions.

    

    It offers a comprehensive and accessible treatment of the theory of algorithms and complexity—the elegant body of concepts and methods developed by computer scientists over the past 30 years for studying the performance and limitations of computer algorithms. The book is self-contained in that it develops all necessary mathematical prerequisites from such diverse fields such as computability, logic, number theory and probability.

    It was the first trip across an engineering marvel that had taken nearly fourteen years to construct. The woman's husband was the chief engineer, and he knew all about the dangerous new technique involved. The woman insisted she learn as well. When he fell ill mid-construction, her knowledge came in handy. She supervised every aspect of the project while he was bedridden, and she continued to learn about things only men were supposed to know:math,science,engineering.Women weren't supposed to be engineers. But this woman insisted she could do it all, and her hard work helped to create one of the most iconic landmarks in the world. This is the story of Emily Roebling, the secret engineer behind the Brooklyn Bridge, from author-illustrator Rachel Dougherty.

    But how can you get started working in a wide-ranging, interdisciplinary field that’s so clouded in hype? This insightful book, based on Columbia University’s Introduction to Data Science class, tells you what you need to know.In many of these chapter-long lectures, data scientists from companies such as Google, Microsoft, and eBay share new algorithms, methods, and models by presenting case studies and the code they use. If you’re familiar with linear algebra, probability, and statistics, and have programming experience, this book is an ideal introduction to data science.Topics include:Statistical inference, exploratory data analysis, and the data science processAlgorithmsSpam filters, Naive Bayes, and data wranglingLogistic regressionFinancial modelingRecommendation engines and causalityData visualizationSocial networks and data journalismData engineering, MapReduce, Pregel, and HadoopDoing Data Science is collaboration between course instructor Rachel Schutt, Senior VP of Data Science at News Corp, and data science consultant Cathy O’Neil, a senior data scientist at Johnson Research Labs, who attended and blogged about the course.

    

    This friendly, easy-to-read guide gently introduces you to the most commonly used features of SAS software plus a whole lot more! Authors Lora Delwiche and Susan Slaughter have revised the text to include concepts of the Output Delivery System; the STYLE= option in the PRINT, REPORT, and TABULATE procedures; ODS HTML, RTF, PRINTER, and OUTPUT destinations; PROC REPORT; more on PROC TABULATE; exporting data; and the colon modifier for informats. You'll find clear and concise explanations of basic SAS concepts (such as DATA and PROC steps), inputting data, modifying and combining data sets, summarizing and presenting data, basic statistical procedures, and debugging SAS programs. Each topic is presented in a self-contained, two-page layout complete with examples and graphics. This format enables new users to get up and running quickly, while the examples allow you to type in the program and see it work!

     Neural networks are a key element of deep learning and artificial intelligence, which today is capable of some truly impressive feats. Yet too few really understand how neural networks actually work. This guide will take you on a fun and unhurried journey, starting from very simple ideas, and gradually building up an understanding of how neural networks work. You won't need any mathematics beyond secondary school, and an accessible introduction to calculus is also included. The ambition of this guide is to make neural networks as accessible as possible to as many readers as possible - there are enough texts for advanced readers already! You'll learn to code in Python and make your own neural network, teaching it to recognise human handwritten numbers, and performing as well as professionally developed networks. Part 1 is about ideas. We introduce the mathematical ideas underlying the neural networks, gently with lots of illustrations and examples. Part 2 is practical. We introduce the popular and easy to learn Python programming language, and gradually builds up a neural network which can learn to recognise human handwritten numbers, easily getting it to perform as well as networks made by professionals. Part 3 extends these ideas further. We push the performance of our neural network to an industry leading 98% using only simple ideas and code, test the network on your own handwriting, take a privileged peek inside the mysterious mind of a neural network, and even get it all working on a Raspberry Pi. All the code in this has been tested to work on a Raspberry Pi Zero.

    I have taught these simple processes to men and women all over the world, and recently over a thousand men and women of all religious affiliations attended a special class in Los Angeles where I presented the highlights of what is offered in the pages of this book. Many came from distances of two hundred miles for each class lesson. The special features of this book will appeal to you because they show you why oftentimes you get the opposite of what you prayed for and reveal to you the reasons why. People have asked me in all parts of the world and thousands of times, ?Why is it I have prayed and prayed and got no answer?? In this book you will find the reasons for this common complaint. The many ways of impressing the subconscious mind and getting the right answers make this an extraordinarily valuable book and an ever present help in time of trouble.

    For outsiders, Pyrrus usually means a quick and painful death, but DinAlt is fleeing the crooked casino masters of Cassylia - where he just broke the bank. But DinAlt is not prepared for the hellish Pyrrus, where every living thing seems bent on exterminating mankind.In DEATHWORLD 2 (originally published as THE ETHICAL ENGINEER), Jason DinAlt finds himself on a hostile, barbarian planet where technology and civilization have almost disappeared. Using his skills, DinAlt literally reinvents the wheel in his quest to escape and return to his friends on Pyrrus.

    

    It provides a concise and relevant treatment of inorganic chemistry and is written with such clarity that it is undoubtedly among the easiest to read of its competitors." Content "Atomic structure and the Periodic table Introduction to bonding The ionic bond The covalent bond The metallic bond General properties of the elements Coordination compounds Hydrogen and the hydrides Group 1 - The alkali metals The chlor-alkali industry Group 2 - The alkaline earth elements The group 13 elements The group 14 elements The group 15 elements Group 16 - the chalcogens Group 17 - the halogens Group 18 - the noble gases An introduction to the transition elements Group 3 - The scandium group Group 4 - The titanium group Group 5 - The vanadium group Group 6 - The chromium group Group 7 - The manganese group Group 8 - The iron group Group 9 - The cobalt group Group 10 - The nickel Group. Group 11 - The copper group: Coinage metals. Group 12 - The zinc group The lanthanide series. The actinides."

    Several resources exist for individual pieces of this data science stack, but only with the Python Data Science Handbook do you get them all—IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and other related tools.Working scientists and data crunchers familiar with reading and writing Python code will find this comprehensive desk reference ideal for tackling day-to-day issues: manipulating, transforming, and cleaning data; visualizing different types of data; and using data to build statistical or machine learning models. Quite simply, this is the must-have reference for scientific computing in Python.With this handbook, you’ll learn how to use: * IPython and Jupyter: provide computational environments for data scientists using Python * NumPy: includes the ndarray for efficient storage and manipulation of dense data arrays in Python * Pandas: features the DataFrame for efficient storage and manipulation of labeled/columnar data in Python * Matplotlib: includes capabilities for a flexible range of data visualizations in Python * Scikit-Learn: for efficient and clean Python implementations of the most important and established machine learning algorithms

    Find out how her passion for math and the Cherokee values she was raised with shaped her life and work. Cherokee author Traci Sorell and Métis illustrator Natasha Donovan trace Ross's journey from being the only girl in a high school math class to becoming a teacher to pursuing an engineering degree, joining the top-secret Skunk Works division of Lockheed, and being a mentor for Native Americans and young women interested in engineering. In addition, the narrative highlights Cherokee values including education, working cooperatively, remaining humble, and helping ensure equal opportunity and education for all.

    A step-by-step visual journey through the mathematics of neural networks, and making your own using Python and Tensorflow.