In this short ebook, Scott Rank distills the principles that helped him go from crippling writer’s block to writing 500-1000 words a day.In this book you will learn the following: A simple daily habit that will help you start writing your dissertationHow to make it impossible not to write everydayHow to write even if all your research isn’t finishedHow to get the most out of your advisor meetingsHow to get your friends actively help you finish, even if they aren’t academics.

    

    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.

    Sometimes the recipe will require you to mix the ingredients, but usually you don’t want to mix them. Young or old, dump cakes are a favorite dessert to make.

    

    It covered jazz, of course, but it also included Davis’s ruminations on race, politics and culture. Fascinated, Hef sent the writer—future Pulitzer-Prize-winning author Alex Haley, an unknown at the time—back to glean even more opinion and insight from Davis. The resulting exchange, published in the September 1962 issue, became the first official Playboy Interview and kicked off a remarkable run of public inquisition that continues today—and that has featured just about every cultural titan of the last half century.To celebrate the Interview’s 50th anniversary, the editors of Playboy have culled 50 of its most (in)famous Interviews and will publish them over the course of 50 weekdays (from September 4, 2012 to November 12, 2012) via Amazon’s Kindle Direct platform. Here is that first Interview with Miles Davis.

    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.

    The authors' comprehensive experience in legal practice, banking and teaching have enabled them to provide a condensed and easy to understand coverage of business law principles and areas of interest related thereto.

    Most important, it provides a wealth of examples for readers to model for everything from online journal articles to supplemental data sets and measurement instruments to books, videos, apps, websites, podcasts, blog posts, and social media. Approximately 70 examples are provided for readers to consider as they learn how to create reliable references for electronic sources.Students and other writers will find this guide indispensable as well as convenient to download and use when creating a reference list.

    This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience, R for Data Science is designed to get you doing data science as quickly as possible. Authors Hadley Wickham and Garrett Grolemund guide you through the steps of importing, wrangling, exploring, and modeling your data and communicating the results. You’ll get a complete, big-picture understanding of the data science cycle, along with basic tools you need to manage the details. Each section of the book is paired with exercises to help you practice what you’ve learned along the way. You’ll learn how to: Wrangle—transform your datasets into a form convenient for analysis Program—learn powerful R tools for solving data problems with greater clarity and ease Explore—examine your data, generate hypotheses, and quickly test them Model—provide a low-dimensional summary that captures true "signals" in your dataset Communicate—learn R Markdown for integrating prose, code, and results

    "What They Did There: Profiles From the Battle of Gettysburg" offers a unique view of its subject, telling the story of the battle not through convention narrative but via 170 mini-bios of not only combatants blue and gray, but of civilians, doctors, nurses, artists, photographers, Samaritans; saints, sinners and the moral terrain in-between.

    More than a manifesto, The Code of Extraordinary Change cracks life wide open, taking you to a place where you're confident, capable and compelled to get out there and put a you-shaped dent in the universe.Containing a set of principles, ideas and specific actions learned from over 10 years of experience in coaching individuals on being naturally self-confident, the Code is a model for building natural confidence and creating and sustaining meaningful change.Get the Code of Extraordinary Change now and go dent the universe.

    We all know one! They like to groan and grumble, offering their own commentary on the shortcomings of modern life. Whether it is queues at the supermarket, the state of the health system, the price of a pint these days, the hairstyles of teenagers, or the number of Maltesers you actually get in a bag, there is always something that will get their goat. 'The Grumpy Old Git's Guide to Life' is a hilarious celebration of all these grumps, how to identify one, what exactly they find so irritating and why we find their rants quite so amusing.

    This book gives you a solid understanding of statistics without being too simple, yet without the numbing complexity of most college texts. You get a firm grasp of the fundamentals and a hands-on understanding of how to apply them before moving on to the more advanced material that follows. Each chapter presents you with easy-to-follow descriptions illustrated by graphics, formulas, and plenty of solved examples. Before you know it, you'll learn to apply statistical reasoning and statistical techniques, from basic concepts of probability and hypothesis testing to multivariate analysis. Organized into four distinct sections, Statistics in a Nutshell offers you:Introductory material: Different ways to think about statistics Basic concepts of measurement and probability theoryData management for statistical analysis Research design and experimental design How to critique statistics presented by others Basic inferential statistics: Basic concepts of inferential statistics The concept of correlation, when it is and is not an appropriate measure of association Dichotomous and categorical data The distinction between parametric and nonparametric statistics Advanced inferential techniques: The General Linear Model Analysis of Variance (ANOVA) and MANOVA Multiple linear regression Specialized techniques: Business and quality improvement statistics Medical and public health statistics Educational and psychological statistics Unlike many introductory books on the subject, Statistics in a Nutshell doesn't omit important material in an effort to dumb it down. And this book is far more practical than most college texts, which tend to over-emphasize calculation without teaching you when and how to apply different statistical tests. With Statistics in a Nutshell, you learn how to perform most common statistical analyses, and understand statistical techniques presented in research articles. If you need to know how to use a wide range of statistical techniques without getting in over your head, this is the book you want.

    This highly anticipated fourth edition of the most ...Download Link : readmeaway.com/download?i=0128042915            0128042915 Data Mining: Practical Machine Learning Tools and Techniques (Morgan Kaufmann Series in Data Management Systems) PDF by Ian H. WittenRead Data Mining: Practical Machine Learning Tools and Techniques (Morgan Kaufmann Series in Data Management Systems) PDF from Morgan Kaufmann,Ian H. WittenDownload Ian H. Witten's PDF E-book Data Mining: Practical Machine Learning Tools and Techniques (Morgan Kaufmann Series in Data Management Systems)