Wilson has distilled sixty years of teaching into a book for students, young and old. Reflecting on his coming-of-age in the South as a Boy Scout and a lover of ants and butterflies, Wilson threads these twenty-one letters, each richly illustrated, with autobiographical anecdotes that illuminate his career--both his successes and his failures--and his motivations for becoming a biologist. At a time in human history when our survival is more than ever linked to our understanding of science, Wilson insists that success in the sciences does not depend on mathematical skill, but rather a passion for finding a problem and solving it. From the collapse of stars to the exploration of rain forests and the oceans' depths, Wilson instills a love of the innate creativity of science and a respect for the human being's modest place in the planet's ecosystem in his readers.

    The complexity of nature's shapes differs in kind, not merely degree, from that of the shapes of ordinary geometry, the geometry of fractal shapes.Now that the field has expanded greatly with many active researchers, Mandelbrot presents the definitive overview of the origins of his ideas and their new applications. The Fractal Geometry of Nature is based on his highly acclaimed earlier work, but has much broader and deeper coverage and more extensive illustrations.

    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

    -Emest Hemingway In October 1984, the weak writing in a scientific report made national news. The report, which outlined safety procedures during a nuclear attack, advised industrial workers "to don heavy clothes and immerse themselves in a large body of water. " The logic behind this advice was sound: Water is a good absorber of heat, neutrons, and gamma rays. Unfortunately, the way the advice was worded was unclear. Was everyone supposed to be com- up for air? Be- pletely submerged? Was it safe to come sides being unclear, the writing conveyed the wrong im- pression to the public. The report came across as saying "go jump in a lake"-not the impression you want to give someone spending thousands of dollars to fund your re- search. Chances are that Dan Rather will not quote sentences from your documents on national television, no matter how weak the writing iso Still, your writing is important. On a personal level, your writing is the principal way in which people learn about your work. When you commu- nicate weIl, you receive credit for that work. When you do not communicate weIl or are too slow to communi- cate, the credit often go es to someone else. On a larger level, your writing and the writing of other scientists and vii viii Foreword engineers influenees publie poliey about scienee and en- gineering.

    Throughout, the emphasis is on promoting a plain English style. This little book can help you communicate more effectively by showing you how to enliven your sentences.

    L. Doctorow, and Frank Rich, into a useful guide not just for writers but for everyone who wants to put their best foot forward in writing prose. Dreyer offers lessons on the ins and outs of punctuation and grammar, including how to navigate the words he calls "the confusables," like tricky homophones; the myriad ways to use (and misuse) a comma; and how to recognize--though not necessarily do away with--the passive voice. (Hint: If you can plausibly add "by zombies" to the end of a sentence, it's passive.) People are sharing their writing more than ever--on blogs, on Twitter--and this book lays out, clearly and comprehensibly, everything writers can do to keep readers focused on the real reason writers write: to communicate their ideas clearly and effectively. Chock-full of advice, insider wisdom, and fun facts on the rules (and nonrules) of the English language, this book will prove invaluable to everyone who wants to shore up their writing skills, mandatory for people who spend their time editing and shaping other people's prose, and--perhaps best of all--an utter treat for anyone who simply revels in language.

    This long-awaited revision contains changes throughout the text. There are new implementations of most of the major programming systems in the book, including the interpreters and compilers, and the authors have incorporated many small changes that reflect their experience teaching the course at MIT since the first edition was published. A new theme has been introduced that emphasizes the central role played by different approaches to dealing with time in computational models: objects with state, concurrent programming, functional programming and lazy evaluation, and nondeterministic programming. There are new example sections on higher-order procedures in graphics and on applications of stream processing in numerical programming, and many new exercises. In addition, all the programs have been reworked to run in any Scheme implementation that adheres to the IEEE standard.

    Shattering the myth of muses, higher powers, even creative “types,” Jonah Lehrer demonstrates that creativity is not a single gift possessed by the lucky few. It’s a variety of distinct thought processes that we can all learn to use more effectively.Lehrer reveals the importance of embracing the rut, thinking like a child, daydreaming productively, and adopting an outsider’s perspective (travel helps). He unveils the optimal mix of old and new partners in any creative collaboration, and explains why criticism is essential to the process. Then he zooms out to show how we can make our neighborhoods more vibrant, our companies more productive, and our schools more effective.You’ll learn about Bob Dylan’s writing habits and the drug addictions of poets. You’ll meet a Manhattan bartender who thinks like a chemist, and an autistic surfer who invented an entirely new surfing move. You’ll see why Elizabethan England experienced a creative explosion, and how Pixar’s office space is designed to spark the next big leap in animation.Collapsing the layers separating the neuron from the finished symphony, Imagine reveals the deep inventiveness of the human mind, and its essential role in our increasingly complex world. http://www.jonahlehrer.com/

    Le Guin generously shares the accumulated wisdom of a lifetime's work.

    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.""

    Snow described science and the humanities as "two cultures," separated by a "gulf of mutual incomprehension." And the humanists had all the cultural power--the low prestige of science, Snow argued, left Western leaders too little educated in scientific subjects that were increasingly central to world problems: the elementary physics behind nuclear weapons, for instance, or the basics of plant science needed to feed the world's growing population.Now, Chris Mooney and Sheril Kirshenbaum, a journalist-scientist team, offer an updated "two cultures" polemic for America in the 21st century. Just as in Snow's time, some of our gravest challenges--climate change, the energy crisis, national economic competitiveness--and gravest threats--global pandemics, nuclear proliferation--have fundamentally scientific underpinnings. Yet we still live in a culture that rarely takes science seriously or has it on the radar.For every five hours of cable news, less than a minute is devoted to science; 46 percent of Americans reject evolution and think the Earth is less than 10,000 years old; the number of newspapers with weekly science sections has shrunken by two-thirds over the past several decades. The public is polarized over climate change--an issue where political party affiliation determines one's view of reality--and in dangerous retreat from childhood vaccinations. Meanwhile, only 18 percent of Americans have even met a scientist to begin with; more than half can't name a living scientist role model.For this dismaying situation, Mooney and Kirshenbaum don't let anyone off the hook. They highlight the anti-intellectual tendencies of the American public (and particularly the politicians and journalists who are supposed to serve it), but also challenge the scientists themselves, who despite the best of intentions have often failed to communicate about their work effectively to a broad public--and so have ceded their critical place in the public sphere to religious and commercial propagandists.A plea for enhanced scientific literacy, Unscientific America urges those who care about the place of science in our society to take unprecedented action. We must begin to train a small army of ambassadors who can translate science's message and make it relevant to the media, to politicians, and to the public in the broadest sense. An impassioned call to arms worthy of Snow's original manifesto, this book lays the groundwork for reintegrating science into the public discourse--before it's too late.

    Each chapter is relatively self-contained and can be used as a unit of study. The algorithms are described in English and in a pseudocode designed to be readable by anyone who has done a little programming. The explanations have been kept elementary without sacrificing depth of coverage or mathematical rigor.

    In this book, you’ll learn how many of the most fundamental data science tools and algorithms work by implementing them from scratch. If you have an aptitude for mathematics and some programming skills, author Joel Grus will help you get comfortable with the math and statistics at the core of data science, and with hacking skills you need to get started as a data scientist. Today’s messy glut of data holds answers to questions no one’s even thought to ask. This book provides you with the know-how to dig those answers out. Get a crash course in Python Learn the basics of linear algebra, statistics, and probability—and understand how and when they're used in data science Collect, explore, clean, munge, and manipulate data Dive into the fundamentals of machine learning Implement models such as k-nearest Neighbors, Naive Bayes, linear and logistic regression, decision trees, neural networks, and clustering Explore recommender systems, natural language processing, network analysis, MapReduce, and databases

    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.

    In this fascinating, provocative new book, Kevin Kelly provides an optimistic road map for the future, showing how the coming changes in our lives—from virtual reality in the home to an on-demand economy to artificial intelligence embedded in everything we manufacture—can be understood as the result of a few long-term, accelerating forces. Kelly both describes these deep trends—flowing, screening, accessing, sharing, filtering, remixing, tracking, and questioning—and demonstrates how they overlap and are codependent on one another. These larger forces will completely revolutionize the way we buy, work, learn, and communicate with each other. By understanding and embracing them, says Kelly, it will be easier for us to remain on top of the coming wave of changes and to arrange our day-to-day relationships with technology in ways that bring forth maximum benefits. Kelly’s bright, hopeful book will be indispensable to anyone who seeks guidance on where their business, industry, or life is heading—what to invent, where to work, in what to invest, how to better reach customers, and what to begin to put into place—as this new world emerges.