Get Programming - Learn to code with Python.epub

Table of Contents LEARNING HOW TO PROGRAM Lesson 1 - Why should you learn how to program? Lesson 2 - Basic principles of learning a programming language UNIT 1 - VARIABLES, TYPES, EXPRESSIONS, AND STATEMENTS Lesson 3 - Introducing Python: a programming language Lesson 4 - Variables and expressions: giving names and values to things Lesson 5 - Object types and statements of code 46 Lesson 6 - Capstone project: your first Python program-convert hours to minutes UNIT 2 - STRINGS, TUPLES, AND INTERACTING WITH THE USER Lesson 7 - Introducing string objects: sequences of characters Lesson 8 - Advanced string operations Lesson 9 - Simple error messages Lesson 10 - Tuple objects: sequences of any kind of object Lesson 11 - Interacting with the user Lesson 12 - Capstone project: name mashup UNIT 3 - MAKING DECISIONS IN YOUR PROGRAMS Lesson 13 - Introducing decisions in programs Lesson 14 - Making more-complicated decisions Lesson 15 - Capstone project: choose your own adventure UNIT 4 - REPEATING TASKS Lesson 16 - Repeating tasks with loops Lesson 17 - Customizing loops Lesson 18 - Repeating tasks while conditions hold Lesson 19 - Capstone project: Scrabble, Art Edition UNIT 5 - ORGANIZING YOUR CODE INTO REUSABLE BLOCKS Lesson 20 - Building programs to last Lesson 21 - Achieving modularity and abstraction with functions Lesson 22 - Advanced operations with functions Lesson 23 - Capstone project: analyze your friends UNIT 6 - WORKING WITH MUTABLE DATA TYPES Lesson 24 - Mutable and immutable objects Lesson 25 - Working with lists Lesson 26 - Advanced operations with lists Lesson 27 - Dictionaries as maps between objects Lesson 28 - Aliasing and copying lists and dictionaries Lesson 29 - Capstone project: document similarity UNIT 7 - MAKING YOUR OWN OBJECT TYPES BY USING OBJECT-ORIENTED PROGRAMMING Lesson 30 - Making your own object types Lesson 31 - Creating a class for an object type Lesson 32 - Working with your own object types Lesson 33 - Customizing classes Lesson 34 - Capstone project: card game UNIT 8 - USING LIBRARIES TO ENHANCE YOUR PROGRAMS Lesson 35 - Useful libraries Lesson 36 - Testing and debugging your programs Lesson 37 - A library for graphical user interfaces Lesson 38 - Capstone project: game of tag Appendix A - Answers to lesson exercises Appendix B - Python cheat sheet Appendix C - Interesting Python libraries

Python Machine Learning Blueprints 2nd Edition

Who this book is for This book is for machine learning practitioners, data scientists, and deep learning enthusiasts who want to take their machine learning skills to the next level by building real-world projects. The intermediate-level guide will help you to implement libraries from the Python ecosystem to build a variety of projects addressing various machine learning domains. Knowledge of Python programming and machine learning concepts will be helpful. Table of Contents: The Python Machine Learning Ecosystem Build an App to Find Underpriced Apartments Build an App to Find Cheap Airfares Forecast the IPO Market Using Logistic Regression Create a Custom Newsfeed Predict whether Your Content Will Go Viral Use Machine Learning to Forecast the Stock Market Classifying Images with Convolutional Neural Networks Building a Chatbot Build a Recommendation Engine What's next?

Hands-On Unsupervised Learning Using Python epub格式

Author Ankur Patel provides practical knowledge on how to apply unsupervised learning using two simple, production-ready Python frameworks - scikit-learn and TensorFlow using Keras. With the hands-on examples and code provided, you will identify difficult-to-find patterns in data and gain deeper business insight, detect anomalies, perform automatic feature engineering and selection, and generate synthetic datasets. All you need is programming and some machine learning experience to get started.

Docker in Practice, 2nd Edition

Table of Contents: PART 1 - DOCKER FUNDAMENTALS Chapter 1 Discovering Docker Chapter 2 Understanding Docker: Inside The Engine Room PART 2 - DOCKER AND DEVELOPMENT Chapter 1 Using Docker As A Lightweight Virtual Machine Chapter 2 Building Images Chapter 3 Running Containers Chapter 4 Day-To-Day Docker Chapter 5 Configuration Management: Getting Your House In Order PART 3 - DOCKER AND DEVOPS Chapter 1 Continuous Integration: Speeding Up Your Development Pipeline Chapter 2 Continuous Delivery: A Perfect Fit For Docker Principles Chapter 3 Network Simulation: Realistic Environment Testing Without The Pain PART 4 - ORCHESTRATION FROM A SINGLE MACHINE TO THE CLOUD Chapter 1 A Primer On Container Orchestration Chapter 2 The Data Center As An Os With Docker Chapter 3 Docker Platforms PART 5 - DOCKER IN PRODUCTION Chapter 1 Docker And Security Chapter 2 Plain Sailing: Running Docker In Production Chapter 3 Docker In Production: Dealing With Challenges

Coding Projects in Scratch

Book Description: A straightforward, visual guide that shows young learners how to build their own computer projects using Scratch, a popular free programming language, using fun graphics and easy-to-follow instructions. Kids can animate their favorite characters, build games to play with friends, create silly sound effects, and more with Coding Projects in Scratch. All they need is a desktop or laptop with Adobe 10.2 or later, and an internet connection to download Scratch 2.0. Coding can be done without download on https://scratch.mit.edu. Step-by-step instructions teach essential coding basics and outline 18 fun and exciting projects, including a personalized birthday card; a "tunnel of doom" multiplayer game; a dinosaur dance party animation with flashing lights, music, and dance moves—and much more. The simple, logical steps in Coding Projects in Scratch are fully illustrated with fun pixel art and build on the basics of coding, so that kids can have the skills to make whatever kind of project they can dream up. Supporting STEM education initiatives, computer coding teaches kids how to think creatively, work collaboratively, and reason systematically, and is quickly becoming a necessary and sought-after skill. DK's computer coding books are full of fun exercises with step-by-step guidance, making them the perfect introductory tools for building vital skills in computer programming.

Hands-On Machine Learning with Scikit-Learn, Keras & TensorFlow 2nd Edition

Hands-On Machine Learning with Scikit-Learn and TensorFlow 的第二版。这是Eearly Release版，只有前9章，请谨慎下载。

Get Programming with Go

Table of Contents Unit 0 - GETTING STARTED Chapter 1. Get Ready, Get Set, Go Unit 1 - IMPERATIVE PROGRAMMING Chapter 1. A Glorified Calculator Chapter 2. Loops And Branches Chapter 3. Variable Scope Chapter 4. Capstone: Ticket To Mars Unit 2 - TYPES Chapter 1. Real Numbers Chapter 2. Whole Numbers Chapter 3. Big Numbers Chapter 4. Multilingual Text Chapter 5. Converting Between Types Chapter 6. Capstone: The Vigenère Cipher Unit 3 - BUILDING BLOCKS Chapter 1. Functions Chapter 2. Methods Chapter 3. First-Class Functions Chapter 4. Capstone: Temperature Tables Unit 4 - COLLECTIONS Chapter 1. Arrayed In Splendor Chapter 2. Slices: Windows Into Arrays Chapter 3. A Bigger Slice Chapter 4. The Ever-Versatile Map Chapter 5. Capstone: A Slice Of Life Unit 5 - STATE AND BEHAVIOR Chapter 1. A Little Structure Chapter 2. Go'S Got No Class Chapter 3. Composition And Forwarding Chapter 4. Interfaces Chapter 5. Capstone: Martian Animal Sanctuary Unit 6 - DOWN THE GOPHER HOLE Chapter 1. A Few Pointers Chapter 2. Much Ado About Nil Chapter 3. To Err Is Human Chapter 4. Capstone: Sudoku Rules Unit 7 - CONCURRENT PROGRAMMING Chapter 1. Goroutines And Concurrency Chapter 2. Concurrent State Chapter 3. Capstone: Life On Mars

Machine Learning for Decision Makers

Book Description Take a deep dive into the concepts of machine learning as they apply to contemporary business and management. You will learn how machine learning techniques are used to solve fundamental and complex problems in society and industry. Machine Learning for Decision Makers serves as an excellent resource for establishing the relationship of machine learning with IoT, big data, and cognitive and cloud computing to give you an overview of how these modern areas of computing relate to each other. This book introduces a collection of the most important concepts of machine learning and sets them in context with other vital technologies that decision makers need to know about. These concepts span the process from envisioning the problem to applying machine-learning techniques to your particular situation. This discussion also provides an insight to help deploy the results to improve decision-making. The book uses case studies and jargon busting to help you grasp the theory of machine learning quickly. You'll soon gain the big picture of machine learning and how it fits with other cutting-edge IT services. This knowledge will give you confidence in your decisions for the future of your business. What You Will Learn Discover the machine learning, big data, and cloud and cognitive computing technology stack Gain insights into machine learning concepts and practices Understand business and enterprise decision-making using machine learning Absorb machine-learning best practices Who This Book Is For Managers tasked with making key decisions who want to learn how and when machine learning and related technologies can help them. Table of Contents Chapter 1: Let’s Integrate with Machine Learning Chapter 2: The Practical Concepts of Machine Learning Chapter 3: Machine Learning Algorithms and Their Relationship with Modern Technologies Chapter 4: Technology Stack for Machine Learning and Associated Technologies Chapter 5: Industrial Applications of Machine Learning Chapter 6: I Am the Future: Machine Learning in Action Chapter 7: Innovation, KPIs, Best Practices, and More for Machine Learning Chapter 8: Do Not Forget Me: The Human Side of Machine Learning Chapter 9: Let’s Wrap Up: The Final Destination Appendix A: How to Architect and Build a Machine Learning Solution Appendix B: A Holistic Machine Learning and Agile-Based Software Methodology Appendix C: Data Processing Technologies

Build Better Chatbots

Book Description: Learn best practices for building bots by focusing on the technological implementation and UX in this practical book. You will cover key topics such as setting up a development environment for creating chatbots for multiple channels (Facebook Messenger, Skype, and KiK); building a chatbot (design to implementation); integrating to IFTT (If This Then That) and IoT (Internet of Things); carrying out analytics and metrics for chatbots; and most importantly monetizing models and business sense for chatbots. Build Better Chatbots is easy to follow with code snippets provided in the book and complete code open sourced and available to download. With Facebook opening up its Messenger platform for developers, followed by Microsoft opening up Skype for development, a new channel has emerged for brands to acquire, engage, and service customers on chat with chatbots. What You Will Learn Work with the bot development life cycle Master bot UX design Integrate into the bot ecosystem Maximize the business and monetization potential for bots Who This Book Is For Developers, programmers, and hobbyists who have basic programming knowledge. The book can be used by existing chatbot developers to gain a better understanding of analytics and the business side of bots.

Learn Computer Science with Swift

Book Description: Master the basics of solving logic puzzles, and creating algorithms using Swift on Apple platforms. This book is based on the curriculum currently being used in common computer classes. You’ll learn to automate algorithmic processes that scale using Swift in the context of iOS, macOS, tvOS, and watchOS. Begin by understanding how to think computationally: to formulate a computational problem and recognize patterns and ways to validate it. Then jump ahead past the abstractions and conceptual work into using code snippets to build frameworks and write code using Xcode and Swift. Once you have frameworks in place, you’ll learn to use algorithms and structure data. Finally, you’ll see how to bring people into what you’ve built through a useable UI and how UI and code relate. What You’ll Learn Recognize patterns and use abstractions Build code into reusable frameworks Manage code and share version control Solve logic puzzles Who This Book Is For Young professionals interested in learning computer science from an Apple platform standpoint.