This book includes as well an illustrated descriptive of 110 different alien races involved with our planet, detailed information about groups and alliances in this galaxy and precious information, as well as a map of the sky with locations of alien life. This book contains also beautiful messages of hope for humanity. This book has been expected for a long time. It brings support and understanding to all those who have been through the ordeal of alien abduction, answering many questions.

    He’s honest, hardworking, and intent on bringing down a major criminal organization. But he's soon going to have his limits tested. After he finishes an undercover assignment, resulting in the arrest of a major crime boss, he’ll find out just how dirty the bad guys play. His world comes crashing down after an unspeakable tragedy, leaving Jacobs virtually despondent and wondering about his role in the unthinkable act. Jacobs soon realizes that in order to beat a low-life criminal organization like this, he has to fight fire with fire. Will he really throw his badge away and become a one man wrecking crew? Or will he try to get retribution within the confines of the law? One thing’s for certain, the men he’s going up against have severely underestimated the lengths that he’ll go to. And he’ll stop at nothing in order to extract his revenge.

    Gaddis motivates the study of both programming skills and the C++ programming language by presenting all the details needed to understand the "how" and the "why"-but never losing sight of the fact that most beginners struggle with this material. His approach is both gradual and highly accessible, ensuring that students understand the logic behind developing high-quality programs. In Starting Out with C++: From Control Structures through Objects, Gaddis covers control structures, functions, arrays, and pointers before objects and classes. As with all Gaddis texts, clear and easy-to-read code listings, concise and practical real-world examples, and an abundance of exercises appear in every chapter. This text is intended for either a one-semester accelerated introductory course or a traditional two-semester sequence covering C++ programming. This edition is available with MyProgrammingLab, an innovative online homework and assessment tool. Through the power of practice and immediate personalized feedback, MyProgrammingLab helps students fully grasp the logic, semantics, and syntax of programming. � Note: If you are purchasing the standalone text or electronic version, MyProgrammingLab does not come automatically packaged with the text. To purchase MyProgrammingLab, please visit: myprogramminglab.com or you can purchase a package of the physical text + MyProgrammingLab by searching for ISBN 10: 0132774178 / ISBN 13: 9780132774178.� MyProgrammingLab is not a self-paced technology and should only be purchased when required by an instructor.

    However, most discussions of Bayesian inference rely on intensely complex mathematical analyses and artificial examples, making it inaccessible to anyone without a strong mathematical background. Now, though, Cameron Davidson-Pilon introduces Bayesian inference from a computational perspective, bridging theory to practice-freeing you to get results using computing power. Bayesian Methods for Hackers illuminates Bayesian inference through probabilistic programming with the powerful PyMC language and the closely related Python tools NumPy, SciPy, and Matplotlib. Using this approach, you can reach effective solutions in small increments, without extensive mathematical intervention. Davidson-Pilon begins by introducing the concepts underlying Bayesian inference, comparing it with other techniques and guiding you through building and training your first Bayesian model. Next, he introduces PyMC through a series of detailed examples and intuitive explanations that have been refined after extensive user feedback. You'll learn how to use the Markov Chain Monte Carlo algorithm, choose appropriate sample sizes and priors, work with loss functions, and apply Bayesian inference in domains ranging from finance to marketing. Once you've mastered these techniques, you'll constantly turn to this guide for the working PyMC code you need to jumpstart future projects. Coverage includes - Learning the Bayesian "state of mind" and its practical implications - Understanding how computers perform Bayesian inference - Using the PyMC Python library to program Bayesian analyses - Building and debugging models with PyMC - Testing your model's "goodness of fit" - Opening the "black box" of the Markov Chain Monte Carlo algorithm to see how and why it works - Leveraging the power of the "Law of Large Numbers" - Mastering key concepts, such as clustering, convergence, autocorrelation, and thinning - Using loss functions to measure an estimate's weaknesses based on your goals and desired outcomes - Selecting appropriate priors and understanding how their influence changes with dataset size - Overcoming the "exploration versus exploitation" dilemma: deciding when "pretty good" is good enough - Using Bayesian inference to improve A/B testing - Solving data science problems when only small amounts of data are available Cameron Davidson-Pilon has worked in many areas of applied mathematics, from the evolutionary dynamics of genes and diseases to stochastic modeling of financial prices. His contributions to the open source community include lifelines, an implementation of survival analysis in Python. Educated at the University of Waterloo and at the Independent University of Moscow, he currently works with the online commerce leader Shopify.

    Including recipes for champagne celebration cake, sour cream pound cake, lemon basil bundt, bacon cake with bacon sprinkles, and many vegan recipes as well, it also reveals the bakery’s approach to developing new cake flavors and provides techniques for trying this at home.

    His girlfriend, Tracie Andrews, claimed he had been murdered in a road rage attack and, days later, appeared at a press conference making an emotional appeal for witnesses to the crime. During the days following the attack, the horrific truth about what really happened that night became apparent. It was Tracie who had killed Lee and then tried to cover her tracks with a web of lies. In this compelling and harrowing book, Maureen shares the turmoil of a bereaved mother trying to come to terms with the brutal murder of her son while at the same time fighting to bring his killer, who she had welcomed into her home, to justice. She also reveals little-known facts about the investigation and speaks of how her shattered family came through their grief and began to rebuild their lives.

    It covers topics ranging from personal responsibility and career development to architectural techniques for keeping your code flexible and easy to adapt and reuse. Read this book, and you'll learn how toFight software rot; Avoid the trap of duplicating knowledge; Write flexible, dynamic, and adaptable code; Avoid programming by coincidence; Bullet-proof your code with contracts, assertions, and exceptions; Capture real requirements; Test ruthlessly and effectively; Delight your users; Build teams of pragmatic programmers; and Make your developments more precise with automation. Written as a series of self-contained sections and filled with entertaining anecdotes, thoughtful examples, and interesting analogies, The Pragmatic Programmer illustrates the best practices and major pitfalls of many different aspects of software development. Whether you're a new coder, an experienced programmer, or a manager responsible for software projects, use these lessons daily, and you'll quickly see improvements in personal productivity, accuracy, and job satisfaction. You'll learn skills and develop habits and attitudes that form the foundation for long-term success in your career. You'll become a Pragmatic Programmer.

    In 1905 an unknown 26-year-old clerk at the Swiss Patent Office, who had supposedly failed math in school, burst on to the scientific scene and swept away the hidebound theories of the day. The clerk, Albert Einstein, introduced a new and unexpected understanding of the universe and launched the two great revolutions of twentieth-century physics, relativity and quantum mechanics. The obscure origin and wide-ranging brilliance of the work recalled Isaac Newton’s “annus mirabilis” (miracle year) of 1666, when as a 23-year-old seeking safety at his family manor from an outbreak of the plague, he invented calculus and laid the foundations for his theory of gravity. Like Newton, Einstein quickly became a scientific icon--the image of genius and, according to Time magazine, the Person of the Century.The actual story is much more interesting. Einstein himself once remarked that “science as something coming into being ... is just as subjectively, psychologically conditioned as are all other human endeavors.” In this profile, the historian of science L. Randles Lagerstrom takes you behind the myth and into the very human life of the young Einstein. From family rifts and girlfriend troubles to financial hardships and jobless anxieties, Einstein’s early years were typical of many young persons. And yet in the midst of it all, he also saw his way through to profound scientific insights. Drawing upon correspondence from Einstein, his family, and his friends, Lagerstrom brings to life the young Einstein and enables the reader to come away with a fuller and more appreciative understanding of Einstein the person and the origins of his revolutionary ideas.About the cover image: While walking to work six days a week as a patent clerk in Bern, Switzerland, Einstein would pass by the famous "Zytglogge" tower and its astronomical clocks. The daily juxtaposition was fitting, as the relative nature of time and clock synchronization would be one of his revolutionary discoveries in the miracle year of 1905.

    Available here:readmeaway.com/download?i=1593279523The Linux Command Line, 2nd Edition: A Complete Introduction PDF by William ShottsRead The Linux Command Line, 2nd Edition: A Complete Introduction PDF from No Starch Press,William ShottsDownload William Shotts’s PDF E-book The Linux Command Line, 2nd Edition: A Complete Introduction

    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.

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    Tackling the job with skills picked up along the way and enough Redbull to sink a battleship. The stories are real. The patients are real, and the emotions are real. Things I would tell my former student-self: You are going to laugh. You are going to cry. You are going to be scared. You are going to want to quit. You will have PTSD. You are going to see death. But hold on, you got this. It's just a few bumps.

    This guide also helps you understand the many data-mining techniques in use today.Based on an MBA course Provost has taught at New York University over the past ten years, Data Science for Business provides examples of real-world business problems to illustrate these principles. You’ll not only learn how to improve communication between business stakeholders and data scientists, but also how participate intelligently in your company’s data science projects. You’ll also discover how to think data-analytically, and fully appreciate how data science methods can support business decision-making.Understand how data science fits in your organization—and how you can use it for competitive advantageTreat data as a business asset that requires careful investment if you’re to gain real valueApproach business problems data-analytically, using the data-mining process to gather good data in the most appropriate wayLearn general concepts for actually extracting knowledge from dataApply data science principles when interviewing data science job candidates

    Build confidence, ditch your inner critic, and finally write your book with simple habits you can start today. You can read this short read (~7,000 words) in about 30 minutes, so it won't get in the way of the one thing standing between you and your book: Action! Download today and make the book you've dreamed of a reality. Now includes a free sample chapter of David Kadavy's latest book, The Heart to Start.

    The gear you select and how you use it can mean big results—or bigger disappointment.FASTER takes a scientific look at triathlon to see what truly makes you faster—and busts the myths and doublespeak that waste your money and race times. In this fascinating exploration of the forces at play in the swim-bike-run sport, astronautical engineer and triathlete Jim Gourley shows where to find free speed, speed on a budget, and the gear upgrades that are worth it.FASTER offers specific, science-based guidance on the fastest techniques and the most effective gear, answering questions like: •    Which wetsuit is best for me? •    What’s the best way to draft a swimmer? •    Should I buy a lighter bike? •    Deep dish or disc wheels? •    Are lighter shoes faster? •    Who’s right about running technique? Gourley reviews published studies in peer-reviewed journals to show what scientists have learned about swim drafting, pacing the bike leg, race strategy for short and long-course racing, and the fastest ways to handle transitions.FASTER will change how you think about your body, your gear, and the world around you. With science on your side, you'll make the smart calls that will make you a better, faster triathlete.