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The Secrets Of Chatgpt Prompt Engineering For Non Developers
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Book Synopsis The Secrets of ChatGPT Prompt Engineering for Non-Developers by : Cea West
Download or read book The Secrets of ChatGPT Prompt Engineering for Non-Developers written by Cea West and published by Cea West. This book was released on with total page 108 pages. Available in PDF, EPUB and Kindle. Book excerpt: Become a prompt engineer with the help of this practical guide. With broad applicability across various topics such as copywriting, SEO, book writing, fiction, and non-fiction, this comprehensive guide provides valuable insights for anyone interested in exploring the art of prompt engineering. Learn practical strategies to monetize your use of ChatGPT while enhancing your writing and communication skills. Boost the efficiency and productivity of content creation by implementing the actionable knowledge gained from this book.
Book Synopsis LLM Prompt Engineering For Developers by : Aymen El Amri
Download or read book LLM Prompt Engineering For Developers written by Aymen El Amri and published by Independently Published. This book was released on 2023-09 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: A practical approach to Prompt Engineering for developers. Dive into the world of Prompt Engineering agility, optimizing your prompts for dynamic LLM interactions. Learn with hands-on examples from the real world and elevate your developer experience with LLMs. Discover how the right prompts can revolutionize your interactions with LLMs. In "LLM Prompt Engineering For Developers," we take a comprehensive journey into the world of LLMs and the art of crafting effective prompts for them. The guide starts by laying the foundation, exploring the evolution of Natural Language Processing (NLP) from its early days to the sophisticated LLMs we interact with today. You will dive deep into the complexities of models such as GPT models, understanding their architecture, capabilities, and nuances. As we progress, this guide emphasizes the importance of effective prompt engineering and its best practices. While LLMs like ChatGPT (GPT-3.5 and GPT-4) are powerful, their full potential is only realized when they are communicated with effectively. This is where prompt engineering comes into play. It's not simply about asking the model a question; it's about phrasing, context, and understanding the model's logic. Through chapters dedicated to Azure Prompt Flow, LangChain, and other tools, you'll gain hands-on experience in crafting, testing, scoring and optimizing prompts. We'll also explore advanced concepts like Few-shot Learning, Chain of Thought, Perplexity and techniques like ReAct and General Knowledge Prompting, equipping you with a comprehensive understanding of the domain. This guide is designed to be hands-on, offering practical insights and exercises. In fact, as you progress, you'll familiarize yourself with several tools: openai Python library: You will dive into the core of OpenAI's LLMs and learn how to interact and fine-tune models to achieve precise outputs tailored to specific needs. promptfoo: You will master the art of crafting effective prompts. Throughout the guide, we'll use promptfoo to test and score prompts, ensuring they're optimized for desired outcomes. LangChain: You'll explore the LangChain framework, which elevates LLM-powered applications. You'll dive into understanding how a prompt engineer can leverage the power of this tool to test and build effective prompts. betterprompt: Before deploying, it's essential to test. With betterprompt, you'll ensure the LLM prompts are ready for real-world scenarios, refining them as needed. Azure Prompt Flow: You will experience the visual interface of Azure's tool, streamlining LLM-based AI development. You'll design executable flows, integrating LLMs, prompts, and Python tools, ensuring a holistic understanding of the art of prompting. And more! With these tools in your toolkit, you will be well-prepared to craft powerful and effective prompts. The hands-on exercises will help solidify your understanding. Throughout the process, you'll be actively engaged and by the end, not only will you appreciate the power of prompt engineering, but you'll also possess the skills to implement it effectively.
Book Synopsis Deep Learning for Vision Systems by : Mohamed Elgendy
Download or read book Deep Learning for Vision Systems written by Mohamed Elgendy and published by Manning Publications. This book was released on 2020-11-10 with total page 478 pages. Available in PDF, EPUB and Kindle. Book excerpt: How does the computer learn to understand what it sees? Deep Learning for Vision Systems answers that by applying deep learning to computer vision. Using only high school algebra, this book illuminates the concepts behind visual intuition. You'll understand how to use deep learning architectures to build vision system applications for image generation and facial recognition. Summary Computer vision is central to many leading-edge innovations, including self-driving cars, drones, augmented reality, facial recognition, and much, much more. Amazing new computer vision applications are developed every day, thanks to rapid advances in AI and deep learning (DL). Deep Learning for Vision Systems teaches you the concepts and tools for building intelligent, scalable computer vision systems that can identify and react to objects in images, videos, and real life. With author Mohamed Elgendy's expert instruction and illustration of real-world projects, you’ll finally grok state-of-the-art deep learning techniques, so you can build, contribute to, and lead in the exciting realm of computer vision! Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology How much has computer vision advanced? One ride in a Tesla is the only answer you’ll need. Deep learning techniques have led to exciting breakthroughs in facial recognition, interactive simulations, and medical imaging, but nothing beats seeing a car respond to real-world stimuli while speeding down the highway. About the book How does the computer learn to understand what it sees? Deep Learning for Vision Systems answers that by applying deep learning to computer vision. Using only high school algebra, this book illuminates the concepts behind visual intuition. You'll understand how to use deep learning architectures to build vision system applications for image generation and facial recognition. What's inside Image classification and object detection Advanced deep learning architectures Transfer learning and generative adversarial networks DeepDream and neural style transfer Visual embeddings and image search About the reader For intermediate Python programmers. About the author Mohamed Elgendy is the VP of Engineering at Rakuten. A seasoned AI expert, he has previously built and managed AI products at Amazon and Twilio. Table of Contents PART 1 - DEEP LEARNING FOUNDATION 1 Welcome to computer vision 2 Deep learning and neural networks 3 Convolutional neural networks 4 Structuring DL projects and hyperparameter tuning PART 2 - IMAGE CLASSIFICATION AND DETECTION 5 Advanced CNN architectures 6 Transfer learning 7 Object detection with R-CNN, SSD, and YOLO PART 3 - GENERATIVE MODELS AND VISUAL EMBEDDINGS 8 Generative adversarial networks (GANs) 9 DeepDream and neural style transfer 10 Visual embeddings
Book Synopsis Machine Learning Guide for Oil and Gas Using Python by : Hoss Belyadi
Download or read book Machine Learning Guide for Oil and Gas Using Python written by Hoss Belyadi and published by Gulf Professional Publishing. This book was released on 2021-04-09 with total page 478 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine Learning Guide for Oil and Gas Using Python: A Step-by-Step Breakdown with Data, Algorithms, Codes, and Applications delivers a critical training and resource tool to help engineers understand machine learning theory and practice, specifically referencing use cases in oil and gas. The reference moves from explaining how Python works to step-by-step examples of utilization in various oil and gas scenarios, such as well testing, shale reservoirs and production optimization. Petroleum engineers are quickly applying machine learning techniques to their data challenges, but there is a lack of references beyond the math or heavy theory of machine learning. Machine Learning Guide for Oil and Gas Using Python details the open-source tool Python by explaining how it works at an introductory level then bridging into how to apply the algorithms into different oil and gas scenarios. While similar resources are often too mathematical, this book balances theory with applications, including use cases that help solve different oil and gas data challenges. Helps readers understand how open-source Python can be utilized in practical oil and gas challenges Covers the most commonly used algorithms for both supervised and unsupervised learning Presents a balanced approach of both theory and practicality while progressing from introductory to advanced analytical techniques
Book Synopsis MACHINE LEARNING WITH PYTHON by : Abhishek Vijayvargia
Download or read book MACHINE LEARNING WITH PYTHON written by Abhishek Vijayvargia and published by BPB Publications. This book was released on 2018-06-02 with total page 266 pages. Available in PDF, EPUB and Kindle. Book excerpt: DescriptionThis book provides the concept of machine learning with mathematical explanation and programming examples. Every chapter starts with fundamentals of the technique and working example on the real-world dataset. Along with the advice on applying algorithms, each technique is provided with advantages and disadvantages on the data.In this book we provide code examples in python. Python is the most suitable and worldwide accepted language for this. First, it is free and open source. It contains very good support from open community. It contains a lot of library, so you don't need to code everything. Also, it is scalable for large amount of data and suitable for big data technologies.This book:Covers all major areas in Machine Learning.Topics are discussed with graphical explanations.Comparison of different Machine Learning methods to solve any problem.Methods to handle real-world noisy data before applying any Machine Learning algorithm.Python code example for each concept discussed.Jupyter notebook scripts are provided with dataset used to test and try the algorithms ContentsIntroduction to Machine Learning Understanding Python Feature Engineering Data VisualisationBasic and Advanced Regression techniquesClassification Un Supervised LearningText AnalysisNeural Network and Deep Learning Recommendation System Time Series Analysis
Book Synopsis Advanced Deep Learning with TensorFlow 2 and Keras by : Rowel Atienza
Download or read book Advanced Deep Learning with TensorFlow 2 and Keras written by Rowel Atienza and published by Packt Publishing Ltd. This book was released on 2020-02-28 with total page 513 pages. Available in PDF, EPUB and Kindle. Book excerpt: Updated and revised second edition of the bestselling guide to advanced deep learning with TensorFlow 2 and Keras Key FeaturesExplore the most advanced deep learning techniques that drive modern AI resultsNew coverage of unsupervised deep learning using mutual information, object detection, and semantic segmentationCompletely updated for TensorFlow 2.xBook Description Advanced Deep Learning with TensorFlow 2 and Keras, Second Edition is a completely updated edition of the bestselling guide to the advanced deep learning techniques available today. Revised for TensorFlow 2.x, this edition introduces you to the practical side of deep learning with new chapters on unsupervised learning using mutual information, object detection (SSD), and semantic segmentation (FCN and PSPNet), further allowing you to create your own cutting-edge AI projects. Using Keras as an open-source deep learning library, the book features hands-on projects that show you how to create more effective AI with the most up-to-date techniques. Starting with an overview of multi-layer perceptrons (MLPs), convolutional neural networks (CNNs), and recurrent neural networks (RNNs), the book then introduces more cutting-edge techniques as you explore deep neural network architectures, including ResNet and DenseNet, and how to create autoencoders. You will then learn about GANs, and how they can unlock new levels of AI performance. Next, you’ll discover how a variational autoencoder (VAE) is implemented, and how GANs and VAEs have the generative power to synthesize data that can be extremely convincing to humans. You'll also learn to implement DRL such as Deep Q-Learning and Policy Gradient Methods, which are critical to many modern results in AI. What you will learnUse mutual information maximization techniques to perform unsupervised learningUse segmentation to identify the pixel-wise class of each object in an imageIdentify both the bounding box and class of objects in an image using object detectionLearn the building blocks for advanced techniques - MLPss, CNN, and RNNsUnderstand deep neural networks - including ResNet and DenseNetUnderstand and build autoregressive models – autoencoders, VAEs, and GANsDiscover and implement deep reinforcement learning methodsWho this book is for This is not an introductory book, so fluency with Python is required. The reader should also be familiar with some machine learning approaches, and practical experience with DL will also be helpful. Knowledge of Keras or TensorFlow 2.0 is not required but is recommended.
Download or read book The Final Twist written by Jeffery Deaver and published by Penguin. This book was released on 2021-05-11 with total page 418 pages. Available in PDF, EPUB and Kindle. Book excerpt: THE INSPIRATION FOR THE UPCOMING CBS ORIGINAL SERIES TRACKER “The master of ticking-bomb suspense” (People) returns with a devilishly good thriller, and reward seeker Colter Shaw's most personal case to date. Just hours after the harrowing events of The Never Game and The Goodbye Man, Colter Shaw finds himself in San Francisco, where he has taken on the mission his father began years ago: finding a missing courier bag containing evidence that will bring down a corporate espionage firm responsible for hundreds, perhaps thousands, of deaths. Following the enigmatic clues his father left behind, Shaw plays cat and mouse with the company's sadistic enforcers, as he speeds from one gritty neighborhood in the City by the Bay to another. Suddenly, the job takes on a frightening urgency: Only by finding the courier bag can he expose the company and stop the murder of an entire family—slated to die in forty-eight hours. With the help of an unexpected figure from his past, and with the enforcers closing the net, Shaw narrows in on the truth—and learns that the courier bag contains something unexpected: a secret that could only be described as catastrophic. Filled with dozens of twists and reversals, The Final Twist is a nonstop race against time to save the family...and to keep the devastating secret Shaw has uncovered from falling into the wrong hands. CBS, CBS Eye Design, and related logos are trademarks of CBS Broadcasting Inc. Used under license. TRACKER is a trademark of Twentieth Century Fox Film Corporation. Used under license.
Book Synopsis Computers at Risk by : National Research Council
Download or read book Computers at Risk written by National Research Council and published by National Academies Press. This book was released on 1990-02-01 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computers at Risk presents a comprehensive agenda for developing nationwide policies and practices for computer security. Specific recommendations are provided for industry and for government agencies engaged in computer security activities. The volume also outlines problems and opportunities in computer security research, recommends ways to improve the research infrastructure, and suggests topics for investigators. The book explores the diversity of the field, the need to engineer countermeasures based on speculation of what experts think computer attackers may do next, why the technology community has failed to respond to the need for enhanced security systems, how innovators could be encouraged to bring more options to the marketplace, and balancing the importance of security against the right of privacy.
Download or read book DAX Patterns written by Marco Russo and published by SQLBI Corp.. This book was released on 2020-08-10 with total page 514 pages. Available in PDF, EPUB and Kindle. Book excerpt: A pattern is a general, reusable solution to a frequent or common challenge. This book is the second edition of the most comprehensive collection of ready-to-use solutions in DAX, that you can use in Microsoft Power BI, Analysis Services Tabular, and Power Pivot for Excel. The book includes the following patterns: Time-related calculations, Standard time-related calculations, Month-related calculations, Week-related calculations, Custom time-related calculations, Comparing different time periods, Semi-additive calculations, Cumulative total, Parameter table, Static segmentation, Dynamic segmentation, ABC classification, New and returning customers, Related distinct count, Events in progress, Ranking, Hierarchies, Parent-child hierarchies, Like-for-like comparison, Transition matrix, Survey, Basket analysis, Currency conversion, Budget.
Book Synopsis Dive Into Deep Learning by : Joanne Quinn
Download or read book Dive Into Deep Learning written by Joanne Quinn and published by Corwin Press. This book was released on 2019-07-15 with total page 297 pages. Available in PDF, EPUB and Kindle. Book excerpt: The leading experts in system change and learning, with their school-based partners around the world, have created this essential companion to their runaway best-seller, Deep Learning: Engage the World Change the World. This hands-on guide provides a roadmap for building capacity in teachers, schools, districts, and systems to design deep learning, measure progress, and assess conditions needed to activate and sustain innovation. Dive Into Deep Learning: Tools for Engagement is rich with resources educators need to construct and drive meaningful deep learning experiences in order to develop the kind of mindset and know-how that is crucial to becoming a problem-solving change agent in our global society. Designed in full color, this easy-to-use guide is loaded with tools, tips, protocols, and real-world examples. It includes: • A framework for deep learning that provides a pathway to develop the six global competencies needed to flourish in a complex world — character, citizenship, collaboration, communication, creativity, and critical thinking. • Learning progressions to help educators analyze student work and measure progress. • Learning design rubrics, templates and examples for incorporating the four elements of learning design: learning partnerships, pedagogical practices, learning environments, and leveraging digital. • Conditions rubrics, teacher self-assessment tools, and planning guides to help educators build, mobilize, and sustain deep learning in schools and districts. Learn about, improve, and expand your world of learning. Put the joy back into learning for students and adults alike. Dive into deep learning to create learning experiences that give purpose, unleash student potential, and transform not only learning, but life itself.
Book Synopsis Learning OpenCV 4 Computer Vision with Python 3 by : Joseph Howse
Download or read book Learning OpenCV 4 Computer Vision with Python 3 written by Joseph Howse and published by Packt Publishing Ltd. This book was released on 2020-02-20 with total page 364 pages. Available in PDF, EPUB and Kindle. Book excerpt: Updated for OpenCV 4 and Python 3, this book covers the latest on depth cameras, 3D tracking, augmented reality, and deep neural networks, helping you solve real-world computer vision problems with practical code Key Features Build powerful computer vision applications in concise code with OpenCV 4 and Python 3 Learn the fundamental concepts of image processing, object classification, and 2D and 3D tracking Train, use, and understand machine learning models such as Support Vector Machines (SVMs) and neural networks Book Description Computer vision is a rapidly evolving science, encompassing diverse applications and techniques. This book will not only help those who are getting started with computer vision but also experts in the domain. You'll be able to put theory into practice by building apps with OpenCV 4 and Python 3. You'll start by understanding OpenCV 4 and how to set it up with Python 3 on various platforms. Next, you'll learn how to perform basic operations such as reading, writing, manipulating, and displaying still images, videos, and camera feeds. From taking you through image processing, video analysis, and depth estimation and segmentation, to helping you gain practice by building a GUI app, this book ensures you'll have opportunities for hands-on activities. Next, you'll tackle two popular challenges: face detection and face recognition. You'll also learn about object classification and machine learning concepts, which will enable you to create and use object detectors and classifiers, and even track objects in movies or video camera feed. Later, you'll develop your skills in 3D tracking and augmented reality. Finally, you'll cover ANNs and DNNs, learning how to develop apps for recognizing handwritten digits and classifying a person's gender and age. By the end of this book, you'll have the skills you need to execute real-world computer vision projects. What you will learn Install and familiarize yourself with OpenCV 4's Python 3 bindings Understand image processing and video analysis basics Use a depth camera to distinguish foreground and background regions Detect and identify objects, and track their motion in videos Train and use your own models to match images and classify objects Detect and recognize faces, and classify their gender and age Build an augmented reality application to track an image in 3D Work with machine learning models, including SVMs, artificial neural networks (ANNs), and deep neural networks (DNNs) Who this book is for If you are interested in learning computer vision, machine learning, and OpenCV in the context of practical real-world applications, then this book is for you. This OpenCV book will also be useful for anyone getting started with computer vision as well as experts who want to stay up-to-date with OpenCV 4 and Python 3. Although no prior knowledge of image processing, computer vision or machine learning is required, familiarity with basic Python programming is a must.
Book Synopsis The Rust Programming Language (Covers Rust 2018) by : Steve Klabnik
Download or read book The Rust Programming Language (Covers Rust 2018) written by Steve Klabnik and published by No Starch Press. This book was released on 2019-09-03 with total page 561 pages. Available in PDF, EPUB and Kindle. Book excerpt: The official book on the Rust programming language, written by the Rust development team at the Mozilla Foundation, fully updated for Rust 2018. The Rust Programming Language is the official book on Rust: an open source systems programming language that helps you write faster, more reliable software. Rust offers control over low-level details (such as memory usage) in combination with high-level ergonomics, eliminating the hassle traditionally associated with low-level languages. The authors of The Rust Programming Language, members of the Rust Core Team, share their knowledge and experience to show you how to take full advantage of Rust's features--from installation to creating robust and scalable programs. You'll begin with basics like creating functions, choosing data types, and binding variables and then move on to more advanced concepts, such as: Ownership and borrowing, lifetimes, and traits Using Rust's memory safety guarantees to build fast, safe programs Testing, error handling, and effective refactoring Generics, smart pointers, multithreading, trait objects, and advanced pattern matching Using Cargo, Rust's built-in package manager, to build, test, and document your code and manage dependencies How best to use Rust's advanced compiler with compiler-led programming techniques You'll find plenty of code examples throughout the book, as well as three chapters dedicated to building complete projects to test your learning: a number guessing game, a Rust implementation of a command line tool, and a multithreaded server. New to this edition: An extended section on Rust macros, an expanded chapter on modules, and appendixes on Rust development tools and editions.
Book Synopsis Machine Learning with Python for Everyone by : Mark Fenner
Download or read book Machine Learning with Python for Everyone written by Mark Fenner and published by Addison-Wesley Professional. This book was released on 2019-07-30 with total page 1375 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Complete Beginner’s Guide to Understanding and Building Machine Learning Systems with Python Machine Learning with Python for Everyone will help you master the processes, patterns, and strategies you need to build effective learning systems, even if you’re an absolute beginner. If you can write some Python code, this book is for you, no matter how little college-level math you know. Principal instructor Mark E. Fenner relies on plain-English stories, pictures, and Python examples to communicate the ideas of machine learning. Mark begins by discussing machine learning and what it can do; introducing key mathematical and computational topics in an approachable manner; and walking you through the first steps in building, training, and evaluating learning systems. Step by step, you’ll fill out the components of a practical learning system, broaden your toolbox, and explore some of the field’s most sophisticated and exciting techniques. Whether you’re a student, analyst, scientist, or hobbyist, this guide’s insights will be applicable to every learning system you ever build or use. Understand machine learning algorithms, models, and core machine learning concepts Classify examples with classifiers, and quantify examples with regressors Realistically assess performance of machine learning systems Use feature engineering to smooth rough data into useful forms Chain multiple components into one system and tune its performance Apply machine learning techniques to images and text Connect the core concepts to neural networks and graphical models Leverage the Python scikit-learn library and other powerful tools Register your book for convenient access to downloads, updates, and/or corrections as they become available. See inside book for details.
Book Synopsis Super Charge Power BI by : Matt Allington
Download or read book Super Charge Power BI written by Matt Allington and published by Tickling Keys, Inc.. This book was released on 2018-06-01 with total page 342 pages. Available in PDF, EPUB and Kindle. Book excerpt: Power BI is a powerful self-service (and enterprise) business intelligence (BI) tool that was first made generally available by Microsoft in July 2015. Power BI is a complete BI package that covers the end to end BI process including data acquisition (get data), data modelling (prepare/model the data) and data visualisation (analyse the data). And there is a lot of good news about this tool including the fact that the skills needed to succeed with Power BI are fully transferable to Microsoft Excel. There are 3 learning areas required to master everything Power BI Desktop has to offer.1. The M Language - used for data acquisition2. The DAX Language - used to prepare and model data3. Visualisation and analysis - used to present data in a compelling wayPower BI is probably the first commercial grade software product that brings all of these areas into a single software package that is completely accessible to a business user (you don't need to be an IT pro). This book focuses on number 2 above, the DAX language (Data Analysis Expressions). Super Charge Power BI Desktop is the second book written by Matt Allington and is a sister book to his first book Learn to Write DAX (first released Dec 2015). Super Charge Power BI Desktop uses the same learning and practice exercise framework as used in Learn to Write DAX however the entire book is written using the Power BI Desktop user interface. Unfortunately simply reading a book is normally not enough for Excel users wanting to get the most out of Power BI Desktop and to learn the DAX language - most people will also need some practice. Super Charge Power BI Desktop is different to other books - it is written in such a way to clearly explain the concepts of Power BI data modelling while at the same time giving hands-on practice to deeply engage the reader to help the new knowledge and concepts stick. The book first presents the theory, then provides worked through sample exercises demonstrating each of the concepts, and finally it provides the reader with practice exercises and answers to maximize learning retention.
Book Synopsis The Craft and Science of Coffee by : Britta Folmer
Download or read book The Craft and Science of Coffee written by Britta Folmer and published by Academic Press. This book was released on 2016-12-16 with total page 556 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Craft and Science of Coffee follows the coffee plant from its origins in East Africa to its current role as a global product that influences millions of lives though sustainable development, economics, and consumer desire. For most, coffee is a beloved beverage. However, for some it is also an object of scientifically study, and for others it is approached as a craft, both building on skills and experience. By combining the research and insights of the scientific community and expertise of the crafts people, this unique book brings readers into a sustained and inclusive conversation, one where academic and industrial thought leaders, coffee farmers, and baristas are quoted, each informing and enriching each other. This unusual approach guides the reader on a journey from coffee farmer to roaster, market analyst to barista, in a style that is both rigorous and experience based, universally relevant and personally engaging. From on-farming processes to consumer benefits, the reader is given a deeper appreciation and understanding of coffee's complexity and is invited to form their own educated opinions on the ever changing situation, including potential routes to further shape the coffee future in a responsible manner. Presents a novel synthesis of coffee research and real-world experience that aids understanding, appreciation, and potential action. Includes contributions from a multitude of experts who address complex subjects with a conversational approach. Provides expert discourse on the coffee calue chain, from agricultural and production practices, sustainability, post-harvest processing, and quality aspects to the economic analysis of the consumer value proposition. Engages with the key challenges of future coffee production and potential solutions.
Book Synopsis Engineers' Guide to Technical Writing by : Kenneth G. Budinski
Download or read book Engineers' Guide to Technical Writing written by Kenneth G. Budinski and published by ASM International. This book was released on 2001-01-01 with total page 397 pages. Available in PDF, EPUB and Kindle. Book excerpt: Annotation An engineer with experience in the automotive and chemical process industries, Budinski has compiled material he used to train new engineers and technicians in an attempt to get his co-workers to document their work in a reasonable manner. He does not focus on the mechanics of the English language, but on the types of documents that an average technical person will encounter in business, government, or industry. He also thinks that students with no technical background should be able to benefit from the tutorial. c. Book News Inc
Book Synopsis Rails 4 in Action by : Rebecca Skinner
Download or read book Rails 4 in Action written by Rebecca Skinner and published by Simon and Schuster. This book was released on 2015-08-30 with total page 850 pages. Available in PDF, EPUB and Kindle. Book excerpt: Summary Rails 4 in Action is a comprehensive introduction to Rails that guides you hands-on through all you'll need to become a competent and confident Rails developer. In it, you'll master Rails 4 by developing a ticket-tracking application that includes RESTful routing, authentication and authorization, file uploads, email, and more. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Book Rails is a full-stack, open source web framework powered by Ruby. Now in version 4, Rails is mature and powerful, and to use it effectively you need more than a few Google searches. You'll find no substitute for the guru's-eye-view of design, testing, deployment, and other real-world concerns that this book provides. Rails 4 in Action is a hands-on guide to the subject. In this fully revised new edition, you'll master Rails 4 by developing a ticket-tracking application that includes RESTful routing, authentication and authorization, file uploads, email, and more. Learn to design your own APIs and successfully deploy a production-quality application. You'll see test-driven development and behavior-driven development in action throughout the book, just like in a top Rails shop. What's Inside Creating your own APIs Using RSpec and Capybara Emphasis on test-first development Fully updated for Rails 4 About the Reader For readers of this book, a background in Ruby is helpful but not required. No Rails experience is assumed. About the Authors Ryan Bigg, Yehuda Katz, Steve Klabnik, and Rebecca Skinner are contributors to Rails and active members of the Rails community. Table of Contents Ruby on Rails, the framework Testing saves your bacon Developing a real Rails application Oh, CRUD! Nested resources Authentication Basic access control Fine-grained access control File uploading Tracking state Tagging Sending email Deployment Designing an API Rack-based applications
