Learn them fast and learn them well. Have you always wanted to learn to build your own website but are afraid it'll be too difficult for you? Or perhaps you are a blogger who wants to tweak your blog's design, without having to spend money on an expensive theme. This book is for you. You no longer have to waste your time and money learning HTML and CSS from lengthy books, expensive online courses or complicated tutorials. What this book offers... HTML and CSS for Beginners Complex concepts are broken down into simple steps to ensure that you can easily master the two languages even if you have never coded before. Carefully Chosen Examples (with images) Examples are carefully chosen to illustrate all concepts. In addition, images are provided whenever necessary so that you can immediately see the visual effects of various CSS properties. Learn The Languages Fast Concepts are presented in a "to-the-point" style to cater to the busy individual. With this book, you can learn HTML and CSS in just one day and start coding immediately. How is this book different... The best way to learn programming is by doing. End-of-Chapter Exercises Each CSS chapter comes with an end-of-chapter exercise where you get to practice the different CSS properties covered in the chapter and see first hand how different CSS values affect the design of the website. Bonus Project The book also includes a bonus project that requires the application of all the HTML and CSS concepts taught previously. Working through the project will not only give you an immense sense of achievement, it’ll also help you see how the various concepts tie together. Are you ready to dip your toes into the exciting world of web development? This book is for you. Click the BUY button and download it now. What you'll learn: - What is CSS and HTML? - What software do you need to write and run CSS codes? - What are HTML tags and elements? - What are the commonly used HTML tags and how to use them? - What are HTML IDs and Classes? - What is the basic CSS syntax? - What are CSS selectors? - What are pseudo classes and pseudo elements? - How to apply CSS rules to your website and what is the order of precedence? - What is the CSS box model? - How to position and float your CSS boxes - How to hide HTML content - How to change the background of CSS boxes - How to use the CSS color property to change colors - How to modify text and font of a website - How to create navigation bars - How to create gorgeous looking tables to display your data .. and more... Click the BUY button and download the book now to start learning HTML and CSS now. Learn them fast and learn them well. Tags: ------------ CSS, HTML5, web development, web page design, CSS examples, CSS tutorials, CSS coding, CSS for Dummies

    Instead of wandering through loads of theory, we will understand CSS more practically so that we can design a webpage using CSS. We have used Notepad for the examples in this book. Alternatively, you can also use Notepad++ or any advanced editor. All that you need to do is copy the code and paste it into Notepad. Upon execution, you will get the output as depicted in the screenshots. Screenshots are provided for each sample code. Coding gets better with practice. The examples in this book are compatible with almost every browser. Instead of using the verbatim code, you can modify the code and see the change in the output, thereby understanding the subtle nuances of CSS. By the end of the book, with practice, you can achieve better things and get more acquainted with CSS.

    Proceed step-by-step through five progressively more complex web applications: from a "Hello World" app all the way to a robust Newspaper app with a custom user model, complete user authentication flow, foreign key relationships, and more. Learn current best practices around class-based views, templates, urls, user authentication, testing, and deployment. The material is up-to-date with the latest versions of both Django (2.0) and Python (3.6). TABLE OF CONTENTS: * Introduction * Chapter 1: Initial Setup * Chapter 2: Hello World app * Chapter 3: Pages app * Chapter 4: Message Board app * Chapter 5: Blog app * Chapter 6: Forms * Chapter 7: User Accounts * Chapter 8: Custom User Model * Chapter 9: User Authentication * Chapter 10: Bootstrap * Chapter 11: Password Change and Reset * Chapter 12: Email * Chapter 13: Newspaper app * Chapter 14: Permissions and Authorizations * Chapter 15: Comments * Conclusion

    

    Beginning with an introduction to array formulas, this manual examines topics such as how they differ from ordinary formulas, the benefits and drawbacks of their use, functions that can and cannot handle array calculations, and array constants and functions. Among the practical applications surveyed include how to extract data from tables and unique lists, how to get results that match any criteria, and how to utilize various methods for unique counts. This book contains 529 screen shots.

    

    Python is easy to learn, and it's perfect for exploring topics like statistics, geometry, probability, and calculus. You’ll learn to write programs to find derivatives, solve equations graphically, manipulate algebraic expressions, even examine projectile motion.Rather than crank through tedious calculations by hand, you'll learn how to use Python functions and modules to handle the number crunching while you focus on the principles behind the math. Exercises throughout teach fundamental programming concepts, like using functions, handling user input, and reading and manipulating data. As you learn to think computationally, you'll discover new ways to explore and think about math, and gain valuable programming skills that you can use to continue your study of math and computer science.If you’re interested in math but have yet to dip into programming, you’ll find that Python makes it easy to go deeper into the subject—let Python handle the tedious work while you spend more time on the math.

    No statistical knowledge is required, and your programming skills can range from hobbyist to pro.Along the way, you'll learn about functional and object-oriented programming, running mathematical simulations, and rearranging complex data into simpler, more useful formats. You'll also learn to: Create artful graphs to visualize complex data sets and functions Write more efficient code using parallel R and vectorization Interface R with C/C++ and Python for increased speed or functionality Find new R packages for text analysis, image manipulation, and more Squash annoying bugs with advanced debugging techniques Whether you're designing aircraft, forecasting the weather, or you just need to tame your data, The Art of R Programming is your guide to harnessing the power of statistical computing.

    mean, margin of error, standard deviation, permutations, and correlations-all using Excel

    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.

    Hundreds of thousands of Python developers around the world rely on Python for general-purpose tasks, Internet scripting, systems programming, user interfaces, and product customization. Available on all major computing platforms, including commercial versions of Unix, Linux, Windows, and Mac OS X, Python is portable, powerful and remarkable easy to use.With its convenient, quick-reference format, "Python Pocket Reference," 3rd Edition is the perfect on-the-job reference. More importantly, it's now been refreshed to cover the language's latest release, Python 2.4. For experienced Python developers, this book is a compact toolbox that delivers need-to-know information at the flip of a page. This third edition also includes an easy-lookup index to help developers find answers fast!Python 2.4 is more than just optimization and library enhancements; it's also chock full of bug fixes and upgrades. And these changes are addressed in the "Python Pocket Reference," 3rd Edition. New language features, new and upgraded built-ins, and new and upgraded modules and packages--they're all clarified in detail.The "Python Pocket Reference," 3rd Edition serves as the perfect companion to "Learning Python" and "Programming Python."

    We are living in an age where data comes in abundance, and thanks to the self-learning algorithms from the field of machine learning, we can turn this data into knowledge. Automated speech recognition on our smart phones, web search engines, e-mail spam filters, the recommendation systems of our favorite movie streaming services – machine learning makes it all possible.Thanks to the many powerful open-source libraries that have been developed in recent years, machine learning is now right at our fingertips. Python provides the perfect environment to build machine learning systems productively.This book will teach you the fundamentals of machine learning and how to utilize these in real-world applications using Python. Step-by-step, you will expand your skill set with the best practices for transforming raw data into useful information, developing learning algorithms efficiently, and evaluating results.You will discover the different problem categories that machine learning can solve and explore how to classify objects, predict continuous outcomes with regression analysis, and find hidden structures in data via clustering. You will build your own machine learning system for sentiment analysis and finally, learn how to embed your model into a web app to share with the world

    The vision behind Clojure is of a radically simple language framework holding together a sophisticated collection of programming features. Learning Clojure involves much more than just learning the mechanics of the language. To really get Clojure you need to understand the ideas underlying this structure of framework and features. You need this book: an accessible introduction to Clojure that focuses on the ideas behind the language as well as the practical details of writing code.

    More than 250 challenging practice questions have been completely revised to closely model the format, tone, topics, and difficulty of the real exam. An integrated study system based on proven pedagogy, exam coverage includes step-by-step exercises, special Exam Watch notes, On-the-Job elements, and Self Tests with in-depth answer explanations to help reinforce and teach practical skills.Praise for the author:"Finally A Java certification book that explains everything clearly. All you need to pass the exam is in this book."--Solveig Haugland, Technical Trainer and Former Sun Course Developer"Who better to write a Java study guide than Kathy Sierra, the reigning queen of Java instruction? Kathy Sierra has done it again--here is a study guide that almost guarantees you a certification "--James Cubeta, Systems Engineer, SGI"The thing I appreciate most about Kathy is her quest to make us all remember that we are teaching people and not just lecturing about Java. Her passion and desire for the highest quality education that meets the needs of the individual student is positively unparalleled at SunEd. Undoubtedly there are hundreds of students who have benefited from taking Kathy's classes."--Victor Peters, founder Next Step Education & Software Sun Certified Java Instructor"I want to thank Kathy for the EXCELLENT Study Guide. The book is well written, every concept is clearly explained using a real life example, and the book states what you specifically need to know for the exam. The way it's written, you feel that you're in a classroom and someone is actually teaching you the difficult concepts, but not in a dry, formal manner. The questions at the end of the chapters are also REALLY good, and I am sure they will help candidates pass the test. Watch out for this Wickedly Smart book."-Alfred Raouf, Web Solution Developer, Kemety.Net"The Sun Certification exam was certainly no walk in the park but Kathy's material allowed me to not only pass the exam, but Ace it "--Mary Whetsel, Sr. Technology Specialist, Application Strategy and Integration, The St. Paul Companies

    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