The Pragmatic Programmer: From Journeyman to Master
Andy Hunt - 1999
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.
DAX Formulas for PowerPivot: The Excel Pro's Guide to Mastering DAX
Rob Collie - 2012
Written by the world’s foremost PowerPivot blogger and practitioner, the book’s concepts and approach are introduced in a simple, step-by-step manner tailored to the learning style of Excel users everywhere. The techniques presented allow users to produce, in hours or even minutes, results that formerly would have taken entire teams weeks or months to produce and include lessons on the difference between calculated columns and measures, how formulas can be reused across reports of completely different shapes, how to merge disjointed sets of data into unified reports, how to make certain columns in a pivot behave as if the pivot were filtered while other columns do not, and how to create time-intelligent calculations in pivot tables such as “Year over Year” and “Moving Averages” whether they use a standard, fiscal, or a complete custom calendar. The “pattern-like” techniques and best practices contained in this book have been developed and refined over two years of onsite training with Excel users around the world, and the key lessons from those seminars costing thousands of dollars per day are now available to within the pages of this easy-to-follow guide.
The Elements of Data Analytic Style
Jeffrey Leek - 2015
This book is focused on the details of data analysis that sometimes fall through the cracks in traditional statistics classes and textbooks. It is based in part on the authors blog posts, lecture materials, and tutorials. The author is one of the co-developers of the Johns Hopkins Specialization in Data Science the largest data science program in the world that has enrolled more than 1.76 million people. The book is useful as a companion to introductory courses in data science or data analysis. It is also a useful reference tool for people tasked with reading and critiquing data analyses. It is based on the authors popular open-source guides available through his Github account (https://github.com/jtleek). The paper is also available through Leanpub (https://leanpub.com/datastyle), if the book is purchased on that platform you are entitled to lifetime free updates.
Numbersense: How to Use Big Data to Your Advantage
Kaiser Fung - 2013
Virtually every choice we make hinges on how someone generates data . . . and how someone else interprets it--whether we realize it or not.Where do you send your child for the best education? Big Data. Which airline should you choose to ensure a timely arrival? Big Data. Who will you vote for in the next election? Big Data.The problem is, the more data we have, the more difficult it is to interpret it. From world leaders to average citizens, everyone is prone to making critical decisions based on poor data interpretations.In Numbersense, expert statistician Kaiser Fung explains when you should accept the conclusions of the Big Data experts--and when you should say, Wait . . . what? He delves deeply into a wide range of topics, offering the answers to important questions, such as:How does the college ranking system really work?Can an obesity measure solve America's biggest healthcare crisis?Should you trust current unemployment data issued by the government?How do you improve your fantasy sports team?Should you worry about businesses that track your data?Don't take for granted statements made in the media, by our leaders, or even by your best friend. We're on information overload today, and there's a lot of bad information out there.Numbersense gives you the insight into how Big Data interpretation works--and how it too often doesn't work. You won't come away with the skills of a professional statistician. But you will have a keen understanding of the data traps even the best statisticians can fall into, and you'll trust the mental alarm that goes off in your head when something just doesn't seem to add up.Praise for NumbersenseNumbersense correctly puts the emphasis not on the size of big data, but on the analysis of it. Lots of fun stories, plenty of lessons learned--in short, a great way to acquire your own sense of numbers!Thomas H. Davenport, coauthor of Competing on Analytics and President's Distinguished Professor of IT and Management, Babson CollegeKaiser's accessible business book will blow your mind like no other. You'll be smarter, and you won't even realize it. Buy. It. Now.Avinash Kaushik, Digital Marketing Evangelist, Google, and author, Web Analytics 2.0Each story in Numbersense goes deep into what you have to think about before you trust the numbers. Kaiser Fung ably demonstrates that it takes skill and resourcefulness to make the numbers confess their meaning.John Sall, Executive Vice President, SAS InstituteKaiser Fung breaks the bad news--a ton more data is no panacea--but then has got your back, revealing the pitfalls of analysis with stimulating stories from the front lines of business, politics, health care, government, and education. The remedy isn't an advanced degree, nor is it common sense. You need Numbersense.Eric Siegel, founder, Predictive Analytics World, and author, Predictive AnalyticsI laughed my way through this superb-useful-fun book and learned and relearned a lot. Highly recommended! Tom Peters, author of In Search of Excellence
The Infographic History of the World
Valentina D'Efilippo - 2013
The History of the World, but not as you know it.A new type of history is here – all 13.8 billion years of it, exploded into a visually jaw-dropping feast of facts, trends and timelines that tell you everything you’d ever want to know about the history of the world.From the primordial soup to the technological revolution of the 21st century, interesting stuff has been going on; and ever since prehistoric man scratched the first tally markings into a damp cave wall, we’ve been counting and measuring it all.Which historic warriors conquered the most territory, killed the most people, or had the largest empire?When did everything evolve?Which languages are related to which?What’s been invented and when?Where are we being born, and what are we dying of?Which countries are eating all the food, causing all the pollution and taking all the drugs?A story of civilisation and barbarism, of war and peace, this is history done in a new way – a beautifully designed collection of the most insightful and revealing trends that tell us what the human race has been up to, and where we’re heading.
Clean Architecture
Robert C. Martin - 2017
"Uncle Bob" Martin shows how to bring greater professionalism and discipline to application architecture and design.As with his other books, Martin's Clean Architecture doesn't merely present multiple choices and options, and say "use your best judgment": it tells you what choices to make, and why those choices are critical to your success. Martin offers direct, no-nonsense answers to key architecture and design questions like:What are the best high level structures for different kinds of applications, including web, database, thick-client, console, and embedded apps?What are the core principles of software architecture?What is the role of the architect, and what is he/she really trying to achieve?What are the core principles of software design?How do designs and architectures go wrong, and what can you do about it?What are the disciplines and practices of professional architects and designers?Clean Architecture is essential reading for every software architect, systems analyst, system designer, and software manager — and for any programmer who aspires to these roles or is impacted by their work.
Take Control of the Noisy Class: Chaos to Calm in 15 Seconds (Super-effective classroom management strategies for teachers in today's toughest classrooms)
Rob Plevin - 2019
Packed with powerful, fast-acting techniques – including a novel routine to get any class quiet in 15 seconds or less – this book helps teachers across all age groups connect and succeed with hard-to-reach, reluctant learners.
You’ll d
iscover:
The simple six-step plan to minimise & deal with classroom behaviour problems
How to gain trust & respect from tough, hard-to-reach students
How to put an end to power struggles & confrontation
How to have students follow your instructions… with no need to repeat yourself
The crucial importance of consistency (and how to achieve it)
Quick and easy ways to raise engagement and enjoyment in your lessons
The ‘Clean Slate’ – a step by step method you can use to ‘start over’ with that particularly difficult group of students who won’t do anything you say.
Take Control of the Noisy Class provides hundreds of practical ideas and interventions to end your classroom management struggles & create a thoroughly enjoyable lesson climate for all concerned.
Data Analytics Made Accessible
Anil Maheshwari - 2014
It is a conversational book that feels easy and informative. This short and lucid book covers everything important, with concrete examples, and invites the reader to join this field. The chapters in the book are organized for a typical one-semester course. The book contains case-lets from real-world stories at the beginning of every chapter. There is a running case study across the chapters as exercises. This book is designed to provide a student with the intuition behind this evolving area, along with a solid toolset of the major data mining techniques and platforms. Students across a variety of academic disciplines, including business, computer science, statistics, engineering, and others are attracted to the idea of discovering new insights and ideas from data. This book can also be gainfully used by executives, managers, analysts, professors, doctors, accountants, and other professionals to learn how to make sense of the data coming their way. This is a lucid flowing book that one can finish in one sitting, or can return to it again and again for insights and techniques. Table of Contents Chapter 1: Wholeness of Business Intelligence and Data Mining Chapter 2: Business Intelligence Concepts & Applications Chapter 3: Data Warehousing Chapter 4: Data Mining Chapter 5: Decision Trees Chapter 6: Regression Models Chapter 7: Artificial Neural Networks Chapter 8: Cluster Analysis Chapter 9: Association Rule Mining Chapter 10: Text Mining Chapter 11: Web Mining Chapter 12: Big Data Chapter 13: Data Modeling Primer Appendix: Data Mining Tutorial using Weka
Python Tricks: A Buffet of Awesome Python Features
Dan Bader - 2017
Discover the “hidden gold” in Python’s standard library and start writing clean and Pythonic code today.
Who Should Read This Book:
If you’re wondering which lesser known parts in Python you should know about, you’ll get a roadmap with this book. Discover cool (yet practical!) Python tricks and blow your coworkers’ minds in your next code review.
If you’ve got experience with legacy versions of Python, the book will get you up to speed with modern patterns and features introduced in Python 3 and backported to Python 2.
If you’ve worked with other programming languages and you want to get up to speed with Python, you’ll pick up the idioms and practical tips you need to become a confident and effective Pythonista.
If you want to make Python your own and learn how to write clean and Pythonic code, you’ll discover best practices and little-known tricks to round out your knowledge.
What Python Developers Say About The Book:
"I kept thinking that I wished I had access to a book like this when I started learning Python many years ago." — Mariatta Wijaya, Python Core Developer"This book makes you write better Python code!" — Bob Belderbos, Software Developer at Oracle"Far from being just a shallow collection of snippets, this book will leave the attentive reader with a deeper understanding of the inner workings of Python as well as an appreciation for its beauty." — Ben Felder, Pythonista"It's like having a seasoned tutor explaining, well, tricks!" — Daniel Meyer, Sr. Desktop Administrator at Tesla Inc.
W. E. B. Du Bois's Data Portraits: Visualizing Black America
Whitney Battle-Baptiste - 2018
E. B. Du Bois offered a view into the lives of black Americans, conveying a literal and figurative representation of "the color line." From advances in education to the lingering effects of slavery, these prophetic infographics--beautiful in design and powerful in content--make visible a wide spectrum of black experience.W. E. B. Du Bois's Data Portraits collects the complete set of graphics in full color for the first time, making their insights and innovations available to a contemporary imagination. As Maria Popova wrote, these data portraits shaped how "Du Bois himself thought about sociology, informing the ideas with which he set the world ablaze three years later in The Souls of Black Folk."
Data Feminism
Catherine D’Ignazio - 2020
It has been used to expose injustice, improve health outcomes, and topple governments. But it has also been used to discriminate, police, and surveil. This potential for good, on the one hand, and harm, on the other, makes it essential to ask: Data science by whom? Data science for whom? Data science with whose interests in mind? The narratives around big data and data science are overwhelmingly white, male, and techno-heroic. In Data Feminism, Catherine D'Ignazio and Lauren Klein present a new way of thinking about data science and data ethics—one that is informed by intersectional feminist thought.Illustrating data feminism in action, D'Ignazio and Klein show how challenges to the male/female binary can help challenge other hierarchical (and empirically wrong) classification systems. They explain how, for example, an understanding of emotion can expand our ideas about effective data visualization, and how the concept of invisible labor can expose the significant human efforts required by our automated systems. And they show why the data never, ever “speak for themselves.”Data Feminism offers strategies for data scientists seeking to learn how feminism can help them work toward justice, and for feminists who want to focus their efforts on the growing field of data science. But Data Feminism is about much more than gender. It is about power, about who has it and who doesn't, and about how those differentials of power can be challenged and changed.
Hands-On Machine Learning with Scikit-Learn and TensorFlow
Aurélien Géron - 2017
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
Probability Theory: The Logic of Science
E.T. Jaynes - 1999
It discusses new results, along with applications of probability theory to a variety of problems. The book contains many exercises and is suitable for use as a textbook on graduate-level courses involving data analysis. Aimed at readers already familiar with applied mathematics at an advanced undergraduate level or higher, it is of interest to scientists concerned with inference from incomplete information.
Designing Data-Intensive Applications
Martin Kleppmann - 2015
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
Plastic Cameras: Toying with Creativity
Michelle Bates - 2006
Whether you're an experienced enthusiast or toy camera neophyte, you'll find Plastic Cameras: Toying with Creativity chock full of tantalizing tips, fun facts and, of course, absolutely striking photographs taken with the lowest tech and simplest tools around. I got me a Holga. Now What? Holgas need a little TLC before they're ready to go out in the world and start snapping. Plastic Cameras: Toying with Creativity digs through all the different Holga models available, lays out thier advantages and quirks and helps you get up to speed on all the prep you'll need to do to jump in on the toy-camera revolution. What should I Feed my Holga? Holgas, Dianas, other toy cameras can use many types of film. Plastic Cameras: Toying with Creativity, lays all their pros and cons on the line letting you get some images you want, and some you could just never imagine. Can Holga come out to play?Plastic Cameras: Toying with Creativity will help you steer your way through all the details and quirks of taking wonderful and weird pictures with your toy camera. We'll explore possible subjects and the best way to shoot them and play with all sorts of techniques from vignetting, to multiple exposures, to panoramas, close-ups, movement, night photography, flare, flash, color and more. For the Intrepid Holga-ographerFor the Holga master, we've diagramed and described advanced toy camera modifications and introduce you to a variety of problems, solutions and inventions born from toy cameras' "limitations." What Next?From negatives to prints or pixels, we help you navigate your post-shooting choices.Don't ForgetThe Diana, Banner, Action Sampler, Photo Blaster, and Lensbaby are all toy cameras with their own loveable qualities. We'll look beyond the Holga to show a whole wide world of toys. Artists Artists in this book include: Michael AckermanJonathan BaileyEric Havelock-BaillieJames BalogBetsy BellSusan BowenLaura BurltonDavid BurnettNancy BursonPerry DilbeckJill EnfieldAnnette FournetMegan GreenWesley KennedyTeru KuwayamaMary Ann LynchAnne Arden McDonaldDaniel MillerTed OrlandRobert OwenBecky RamotowskiNancy RexrothFrancisco Mata RosasRichard RossFranco SalmoiraghiMichael SherwinHarvey SteinGordon StettiniusMark SinkKurt SmithSandy SorlienPauline St. Denis;-p r a b u!