If your job requires you to manage and analyze all kinds of data, turn to Head First Data Analysis, where you'll quickly learn how to collect and organize data, sort the distractions from the truth, find meaningful patterns, draw conclusions, predict the future, and present your findings to others. Whether you're a product developer researching the market viability of a new product or service, a marketing manager gauging or predicting the effectiveness of a campaign, a salesperson who needs data to support product presentations, or a lone entrepreneur responsible for all of these data-intensive functions and more, the unique approach in Head First Data Analysis is by far the most efficient way to learn what you need to know to convert raw data into a vital business tool. You'll learn how to:Determine which data sources to use for collecting information Assess data quality and distinguish signal from noise Build basic data models to illuminate patterns, and assimilate new information into the models Cope with ambiguous information Design experiments to test hypotheses and draw conclusions Use segmentation to organize your data within discrete market groups Visualize data distributions to reveal new relationships and persuade others Predict the future with sampling and probability models Clean your data to make it useful Communicate the results of your analysis to your audience Using the latest research in cognitive science and learning theory to craft a multi-sensory learning experience, Head First Data Analysis uses a visually rich format designed for the way your brain works, not a text-heavy approach that puts you to sleep.

    Whether you’re an intermediate-level Python programmer or a student of computational modeling, you’ll delve into examples of complex systems through a series of exercises, case studies, and easy-to-understand explanations.You’ll work with graphs, algorithm analysis, scale-free networks, and cellular automata, using advanced features that make Python such a powerful language. Ideal as a text for courses on Python programming and algorithms, Think Complexity will also help self-learners gain valuable experience with topics and ideas they might not encounter otherwise.Work with NumPy arrays and SciPy methods, basic signal processing and Fast Fourier Transform, and hash tablesStudy abstract models of complex physical systems, including power laws, fractals and pink noise, and Turing machinesGet starter code and solutions to help you re-implement and extend original experiments in complexityExplore the philosophy of science, including the nature of scientific laws, theory choice, realism and instrumentalism, and other topicsExamine case studies of complex systems submitted by students and readers

    On the cusp of decoding brain signals that govern motor skills, they are developing miraculous technologies to enable paraplegics and wounded soldiers to move prosthetic limbs, and the rest of us to manipulate computers and other objects through thought alone. These fiercely competitive scientists are vying for Defense Department and venture capital funding, prestige, and great wealth. Part life-altering cure, part science fiction, part military dream, these cutting-edge brain-computer interfaces promise to improve lives—but also hold the potential to augment soldiers' combat capabilities. In The Brain Electric, Malcolm Gay follows the dramatic emergence of these technologies, taking us behind the scenes into the operating rooms, start-ups, and research labs where the future is unfolding. With access to many of the field's top scientists, Gay illuminates this extraordinary race—where science, medicine, profit, and war converge—for the first time. But this isn't just a story about technology. At the heart of this research is a group of brave, vulnerable patient-volunteers whose lives are given new meaning through participating in these experiments. The Brain Electric asks us to rethink our relationship to technology, our bodies, even consciousness itself—challenging our assumptions about what it means to be human.

    Jackson, Sly Stallone, Richard Zanuck, and relatives of an Indonesian dictator and Saudi Arabia’s king). He then flashes back to the creation of this fabled district, built on dusty lima bean fields and carved out of the rugged impassible mountains between the city and the sea. Using the century-long evolution from adobe huts to $100 million mansions as the baseline of the story, he reveals how a few powerful and often ruthless oil and railroad magnates imposed their idyllic vision of the good life on the Los Angeles landscape to create the legendary communities known as the Platinum Triangle.            Gross goes on to give vivid, riveting accounts of the most lavish of the many lavish houses that started springing up almost immediately (with only a brief slowdown during the Depression). But the stories of these homes are just a window onto the lives of their owners and occupants over the course of the twentieth century, and onto the bigger story of a people and a storied region that have become, in Gross’s words, “the Mecca of self-invention.”            As one might imagine, there is a truly glittering cast of characters. Apart from the many Hollywood stars who have passed through these houses—Douglas Fairbanks Jr., Harold Lloyd, Marilyn Monroe, Jayne Mansfield, George Hamilton, Tony Curtis, Cher, to name just a few—you will meet decadent Spanish land-grant families, desperado oilmen and railroad titans, the country’s first all-powerful corporate legends, con men and pyramid schemers, porn magnates, and Arab potentates, not to mention contemporary tabloid luminaries from the worlds of business and entertainment. Taken altogether, their stories read like a cross between Valley of the Dolls, Hollywood Babylon, and Gross’s own 740 Park—with a little of the film Chinatown thrown in too.             Los Angeles provides Michael Gross with his broadest canvas yet; Unreal Estate will surprise, fascinate, and most of all entertain you with a story you don’t know about a place you think you do.

    David Agus tackles these fundamental questions and dismantles misperceptions about what “health” really means. Presenting an eye-opening picture of the human body and all the ways it works—and fails—Dr. Agus shows us how a new perspective on our individual health will allow us to achieve a long, vigorous life. Offering insights and access to powerful new technologies that promise to transform medicine, Dr. Agus emphasizes his belief that there is no “right” answer, no master guide that is “one size fits all.” Each one of us must get to know our bodies in uniquely personal ways, and he shows us exactly how to do that. A bold call for all of us to become our own personal health advocates, The End of Illness is a moving departure from orthodox thinking.

    Fundamentals of Biostatistics with CD-Rom.

     So why can it be so hard to achieve the results we crave? Working harder rarely has the desired effect. The answer is to work smarter, and with – not against – our natural strengths. Mindset with Muscle takes you on a different transformation journey. Rather than hitting the gym and obsessing about success, this book brings you ‘sets and reps for the brain’. When you read this book, and implement Jamie Alderton’s proven strategies, you will be able to: Develop your brain and build new habits that hard-wire you for success Map out exactly what you need to do in order to achieve your physical, business and financial goals Move forward confidently and take action to build the business, body and lifestyle of your dreams Finally get in the best physical and mental shape of your life Know with certainty you can achieve whatever it is you set out to do Mindset with Muscle urges you to wake up and realise you have the choice in life to achieve pretty much anything you set your mind to.

    It's a great project for families and foodies alike, and all you need to start off is this book, a specialist mushroom growing kit, and a small space in which to grow them!In this book I aim to teach you the basics that you need to know to grow mushrooms at home. You'll take a step back in time and learn about the history of mushrooms as food, and why it has taken centuries for home mushroom growing to really catch on. I'll let you know exactly which are the best types of mushrooms for you to start with. If you aren't sure what tools you'll need, don't worry - this book has that covered too. And I'll explain how to make sure that your mushrooms grow quickly and pest free, and the best ways to harvest, preserve and store your crop.But where should you grow your mushrooms? That's a good question! Contained within the pages of this book are tips on how to set up a mushroom patch in your back yard, as well as how to grow them inside. Is it really better to grow them completely in the dark? You are about to find out!So, whether you like shiitakes, portobellos or oyster mushrooms, stop buying them in stores. I'll teach you how to grow your own and keep your entire family well supplied.In as little as a few weeks you can have the perfect fresh mushrooms grown and ready to eat. Yum!This easy to read, beginners book, summarizes the essential information I have learned over the years, and is written to help you decide if mycology is for you, and if so, which route to take.

    

    Everything around us, including matter, is energy. A deep look into the mysteries of the subatomic world – the particles that make up the atom – provides answers to basic questions about how the universe works. To solve the future of mankind’s energy needs we need to understand the basic building blocks of the universe, including the atom and its parts. By exploring the subatomic world we’ll find more answers to our questions about time, forces like gravity and the matter that surrounds us. More importantly, we’ll find new ways to tap into the energy that exists around us to power our growing needs. In a new branch of particle physics, where tiny particles are thought of as energy waves, we find new answers that may help us in our quest to find alternative energy sources.

    Some of the objects are described by future historians; others through found materials, short stories, or dialogues. All come from a very real future.

    Machine learning provides these, developing methods that can automatically detect patterns in data and then use the uncovered patterns to predict future data. This textbook offers a comprehensive and self-contained introduction to the field of machine learning, based on a unified, probabilistic approach.The coverage combines breadth and depth, offering necessary background material on such topics as probability, optimization, and linear algebra as well as discussion of recent developments in the field, including conditional random fields, L1 regularization, and deep learning. The book is written in an informal, accessible style, complete with pseudo-code for the most important algorithms. All topics are copiously illustrated with color images and worked examples drawn from such application domains as biology, text processing, computer vision, and robotics. Rather than providing a cookbook of different heuristic methods, the book stresses a principled model-based approach, often using the language of graphical models to specify models in a concise and intuitive way. Almost all the models described have been implemented in a MATLAB software package—PMTK (probabilistic modeling toolkit)—that is freely available online. The book is suitable for upper-level undergraduates with an introductory-level college math background and beginning graduate students.

    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.

    

    With it, you'll learn how to write Python programs that work with large collections of unstructured text. You'll access richly annotated datasets using a comprehensive range of linguistic data structures, and you'll understand the main algorithms for analyzing the content and structure of written communication.Packed with examples and exercises, Natural Language Processing with Python will help you: Extract information from unstructured text, either to guess the topic or identify "named entities" Analyze linguistic structure in text, including parsing and semantic analysis Access popular linguistic databases, including WordNet and treebanks Integrate techniques drawn from fields as diverse as linguistics and artificial intelligenceThis book will help you gain practical skills in natural language processing using the Python programming language and the Natural Language Toolkit (NLTK) open source library. If you're interested in developing web applications, analyzing multilingual news sources, or documenting endangered languages -- or if you're simply curious to have a programmer's perspective on how human language works -- you'll find Natural Language Processing with Python both fascinating and immensely useful.