This book is an easy-to-understand and fun reference to this challenging subject. It explains the principles of organic chemistry in simple terms and includes worked-out problems to help readers get up to speed on the basics.

    A light-hearted and informative reminder of all the things that we learnt in school but have since become relegated to the backs of our minds, I Used to Know That features hundreds of important snippets of wisdom, facts, theories, equations, phrases, rules and sayings. A practical guide to turn to when an answer is eluding you, when helping a child with homework or preparing them for the new school year, or maybe just to brush up on trivia for the pub quiz. I Used to Know That covers English Language and Literature, Mathematics, Biology, Chemistry, Physics, History, Geography and General Studies, so never again will you find yourself stumped!

    Previously undocumented, these 23 patterns allow designers to create more flexible, elegant, and ultimately reusable designs without having to rediscover the design solutions themselves.The authors begin by describing what patterns are and how they can help you design object-oriented software. They then go on to systematically name, explain, evaluate, and catalog recurring designs in object-oriented systems. With Design Patterns as your guide, you will learn how these important patterns fit into the software development process, and how you can leverage them to solve your own design problems most efficiently. Each pattern describes the circumstances in which it is applicable, when it can be applied in view of other design constraints, and the consequences and trade-offs of using the pattern within a larger design. All patterns are compiled from real systems and are based on real-world examples. Each pattern also includes code that demonstrates how it may be implemented in object-oriented programming languages like C++ or Smalltalk.

    And yet, disturbingly, in today's so-called information age, pseudoscience is burgeoning with stories of alien abduction, channeling past lives, and communal hallucinations commanding growing attention and respect. As Sagan demonstrates with lucid eloquence, the siren song of unreason is not just a cultural wrong turn but a dangerous plunge into darkness that threatens our most basic freedoms.

    Rombauer self-published the first three thousand copies of Joy of Cooking in 1931, it has become the kitchen bible, with more than 20 million copies in print. This new edition of Joy has been thoroughly revised and expanded by Irma’s great-grandson John Becker and his wife, Megan Scott.John and Megan developed more than six hundred new recipes for this edition, tested and tweaked thousands of classic recipes, and updated every section of every chapter to reflect the latest ingredients and techniques available to today’s home cooks. Their strategy for revising this edition was the same one Irma and Marion employed: Vet, research, and improve Joy’s coverage of legacy recipes while introducing new dishes, modern cooking techniques, and comprehensive information on ingredients now available at farmers’ markets and grocery stores. You will find tried-and-true favorites like Banana Bread Cockaigne, Chocolate Chip Cookies, and Southern Corn Bread—all retested and faithfully improved—as well as new favorites like Chana Masala, Beef Rendang, Megan’s Seeded Olive Oil Granola, and Smoked Pork Shoulder. In addition to a thoroughly modernized vegetable chapter, there are many more vegan and vegetarian recipes, including Caramelized Tamarind Tempeh, Crispy Pan-Fried Tofu, Spicy Chickpea Soup, and Roasted Mushroom Burgers. Joy’s baking chapters now include gram weights for accuracy, along with a refreshed lineup of baked goods like Cannelés de Bordeaux, Rustic No-Knead Sourdough, Ciabatta, Chocolate-Walnut Babka, and Chicago-Style Deep-Dish Pizza, as well as gluten-free recipes for pizza dough and yeast breads. A new chapter on streamlined cooking explains how to economize time, money, and ingredients and avoid waste. You will learn how to use a diverse array of ingredients, from amaranth to za’atar. New techniques include low-temperature and sous vide cooking, fermentation, and cooking with both traditional and electric pressure cookers. Barbecuing, smoking, and other outdoor cooking methods are covered in even greater detail. This new edition of Joy is the perfect combination of classic recipes, new dishes, and indispensable reference information for today’s home cooks. Whether it is the only cookbook on your shelf or one of many, Joy is and has been the essential and trusted guide for home cooks for almost a century. This new edition continues that legacy.

    But what if you could have your computer do them for you?In "Automate the Boring Stuff with Python," you'll learn how to use Python to write programs that do in minutes what would take you hours to do by hand no prior programming experience required. Once you've mastered the basics of programming, you'll create Python programs that effortlessly perform useful and impressive feats of automation to: Search for text in a file or across multiple filesCreate, update, move, and rename files and foldersSearch the Web and download online contentUpdate and format data in Excel spreadsheets of any sizeSplit, merge, watermark, and encrypt PDFsSend reminder emails and text notificationsFill out online formsStep-by-step instructions walk you through each program, and practice projects at the end of each chapter challenge you to improve those programs and use your newfound skills to automate similar tasks.Don't spend your time doing work a well-trained monkey could do. Even if you've never written a line of code, you can make your computer do the grunt work. Learn how in "Automate the Boring Stuff with Python.""

    With it has come vast amounts of data in a variety of fields such as medicine, biology, finance, and marketing. The challenge of understanding these data has led to the development of new tools in the field of statistics, and spawned new areas such as data mining, machine learning, and bioinformatics. Many of these tools have common underpinnings but are often expressed with different terminology. This book describes the important ideas in these areas in a common conceptual framework. While the approach is statistical, the emphasis is on concepts rather than mathematics. Many examples are given, with a liberal use of color graphics. It should be a valuable resource for statisticians and anyone interested in data mining in science or industry. The book's coverage is broad, from supervised learning (prediction) to unsupervised learning. The many topics include neural networks, support vector machines, classification trees and boosting—the first comprehensive treatment of this topic in any book. Trevor Hastie, Robert Tibshirani, and Jerome Friedman are professors of statistics at Stanford University. They are prominent researchers in this area: Hastie and Tibshirani developed generalized additive models and wrote a popular book of that title. Hastie wrote much of the statistical modeling software in S-PLUS and invented principal curves and surfaces. Tibshirani proposed the Lasso and is co-author of the very successful An Introduction to the Bootstrap. Friedman is the co-inventor of many data-mining tools including CART, MARS, and projection pursuit.

    The Quran is composed of verses (Ayat) that make up 114 chapters (suras) of unequal length which are classified either as Meccan (المكية) or Medinan (المدنية) depending upon the place and time of their claimed revelation. Muslims believe the Quran to be verbally revealed through the angel Jibrīl (Gabriel) from God to Muhammad gradually over a period of approximately 23 years beginning on 22 December 609 CE, when Muhammad was 40, and concluding in 632 CE, the year of his death.Muslims regard the Quran as the main miracle of Muhammad, the proof of his prophethood and the culmination of a series of divine messages that started with the messages revealed to Adam, regarded in Islam as the first prophet, and continued with Suhuf Ibrahim (Scrolls of Abraham), the Tawrat (Torah or Pentateuch) of Moses, the Zabur (Tehillim or Book of Psalms) of David, and the Injil (Gospel) of Jesus. The Quran assumes familiarity with major narratives recounted in Jewish and Christian scriptures, summarizing some, dwelling at length on others and in some cases presenting alternative accounts and interpretations of events. The Quran describes itself as a book of guidance, sometimes offering detailed accounts of specific historical events, and often emphasizing the moral significance of an event over its narrative sequence.

    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

    Difficult issues need to be figured out, such as scalability, consistency, reliability, efficiency, and maintainability. In addition, we have an overwhelming variety of tools, including relational databases, NoSQL datastores, stream or batch processors, and message brokers. What are the right choices for your application? How do you make sense of all these buzzwords?In this practical and comprehensive guide, author Martin Kleppmann helps you navigate this diverse landscape by examining the pros and cons of various technologies for processing and storing data. Software keeps changing, but the fundamental principles remain the same. With this book, software engineers and architects will learn how to apply those ideas in practice, and how to make full use of data in modern applications. Peer under the hood of the systems you already use, and learn how to use and operate them more effectively Make informed decisions by identifying the strengths and weaknesses of different tools Navigate the trade-offs around consistency, scalability, fault tolerance, and complexity Understand the distributed systems research upon which modern databases are built Peek behind the scenes of major online services, and learn from their architectures

    But where do they come from? What kind of environment breeds them? What sparks the flash of brilliance? How do we generate the breakthrough technologies that push forward our lives, our society, our culture? Steven Johnson's answers are revelatory as he identifies the seven key patterns behind genuine innovation, and traces them across time and disciplines. From Darwin and Freud to the halls of Google and Apple, Johnson investigates the innovation hubs throughout modern time and pulls out the approaches and commonalities that seem to appear at moments of originality.

    Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally specify all the knowledge that the computer needs. The hierarchy of concepts allows the computer to learn complicated concepts by building them out of simpler ones; a graph of these hierarchies would be many layers deep. This book introduces a broad range of topics in deep learning.The text offers mathematical and conceptual background, covering relevant concepts in linear algebra, probability theory and information theory, numerical computation, and machine learning. It describes deep learning techniques used by practitioners in industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology; and it surveys such applications as natural language processing, speech recognition, computer vision, online recommendation systems, bioinformatics, and videogames. Finally, the book offers research perspectives, covering such theoretical topics as linear factor models, autoencoders, representation learning, structured probabilistic models, Monte Carlo methods, the partition function, approximate inference, and deep generative models.Deep Learning can be used by undergraduate or graduate students planning careers in either industry or research, and by software engineers who want to begin using deep learning in their products or platforms. A website offers supplementary material for both readers and instructors.

    Seasoned researchers and educators Gregory G. Colomb and Joseph M. Williams present an updated third edition of their classic handbook, whose first and second editions were written in collaboration with the late Wayne C. Booth. The Craft of Research explains how to build an argument that motivates readers to accept a claim; how to anticipate the reservations of readers and to respond to them appropriately; and how to create introductions and conclusions that answer that most demanding question, “So what?” The third edition includes an expanded discussion of the essential early stages of a research task: planning and drafting a paper. The authors have revised and fully updated their section on electronic research, emphasizing the need to distinguish between trustworthy sources (such as those found in libraries) and less reliable sources found with a quick Web search. A chapter on warrants has also been thoroughly reviewed to make this difficult subject easier for researchers Throughout, the authors have preserved the amiable tone, the reliable voice, and the sense of directness that have made this book indispensable for anyone undertaking a research project.

    How did the table fork acquire a fourth tine?  What advantage does the Phillips-head screw have over its single-grooved predecessor? Why does the paper clip look the way it does? What makes Scotch tape Scotch?   In this delightful book Henry Petroski takes a microscopic look at artifacts that most of us count on but rarely contemplate, including such icons of the everyday as pins, Post-its, and fast-food "clamshell" containers.  At the same time, he offers a convincing new theory of technological innovation as a response to the perceived failures of existing products—suggesting that irritation, and not necessity, is the mother of invention.

    It takes a fairly traditional approach, emphasizing problem solving, design, and programming as the core skills of computer science. However, these ideas are illustrated using a non-traditional language, namely Python. Although I use Python as the language, teaching Python is not the main point of this book. Rather, Python is used to illustrate fundamental principles of design and programming that apply in any language or computing environment. In some places, I have purposely avoided certain Python features and idioms that are not generally found in other languages. There are already many good books about Python on the market; this book is intended as an introduction to computing. Features include the following: *Extensive use of computer graphics. *Interesting examples. *Readable prose. *Flexible spiral coverage. *Just-in-time object coverage. *Extensive end-of-chapter problems.