Metagenomics is a discipline that enables the genomic study of uncultured microorganisms. Faster, cheaper sequencing technologies and the ability to sequence uncultured microbes sampled directly from their habitats are expanding and transforming our view of the microbial world. Distilling meaningful information from the millions of new genomic sequences presents a serious challenge to bioinformaticians. In cultured microbes, the genomic data come from a single clone, making sequence assembly and annotation tractable. In metagenomics, the data come from heterogeneous microbial communities, sometimes containing more than 10,000 species, with the sequence data being noisy and partial. From sampling, to assembly, to gene calling and function prediction, bioinformatics faces new demands in interpreting voluminous, noisy, and often partial sequence data. Although metagenomics is a relative newcomer to science, the past few years have seen an explosion in computational methods applied to metagenomic-based research. It is therefore not within the scope of this article to provide an exhaustive review. Rather, we provide here a concise yet comprehensive introduction to the current computational requirements presented by metagenomics, and review the recent progress made. We also note whether there is software that implements any of the methods presented here, and briefly review its utility. Nevertheless, it would be useful if readers of this article would avail themselves of the comment section provided by this journal, and relate their own experiences. Finally, the last section of this article provides a few representative studies illustrating different facets of recent scientific discoveries made using metagenomics. Read more

Epigenetics is the most exciting field in biology today, developing our understanding of how and why we inherit certain traits, develop diseases and age, and evolve as a species.   This non-fiction comic book introduces us to genetics, cell biology and the fascinating science of epigenetics, which is rapidly filling in the gaps in our knowledge, allowing us to make huge advances in medicine. We'll look at what identical twins can teach us about the epigenetic effects of our environment and experiences, why certain genes are 'switched on' or off at various stages of embryonic development, and how scientists have reversed the specialization of cells to clone frogs from a single gut cell.   In Introducing Epigenetics, Cath Ennis and Oliver Pugh pull apart the double helix, examining how the epigenetic building blocks and messengers that interpret and edit our genes help to make us, well, us. Read more

This book describes the important ideas in a variety of fields such as medicine, biology, finance, and marketing in a common conceptual framework. While the approach is statistical, the emphasis is on concepts rather than mathematics. Many examples are given, with a liberal use of colour graphics. It is a valuable resource for statisticians and anyone interested in data mining in science or industry. The book's coverage is broad, from supervised learning (prediction) to unsupervised learning. The many topics include neural networks, support vector machines, classification trees and boosting---the first comprehensive treatment of this topic in any book.This major new edition features many topics not covered in the original, including graphical models, random forests, ensemble methods, least angle regression & path algorithms for the lasso, non-negative matrix factorisation, and spectral clustering. There is also a chapter on methods for "wide'' data (p bigger than n), including multiple testing and false discovery rates. Read more

One of the world's leading managers in the field of Artificial Intelligence unveils the secrets to creating synergy between human and artificial intelligence that will revolutionize our world.Today, we are merely at the threshold of the acceleration of the Digital Era. But what will happen in the coming years, when artificial intelligence (AI) is going to dramatically change the world?A machine can use big data to generate information better than humans. However, a machine can’t understand context, doesn’t have feelings or ethics, and can’t think ‘out of the box’. Therefore, rather than prioritize between humans and machines, we should create The Human-Machine Team, which will combine human intelligence and artificial intelligence, creating a ‘super cognition’.Brigadier General Y.S, an expert analyst, technology director, commander of an elite intelligence unit, and winner of the prestigious Israel Defense Prize for his artificial intelligence based anti-terrorism project, wrote his book, The Human-Machine Team, to address how the combination between human and artificial intelligence can solve national security challenges and threats, lead to victory in war, and be a growth engine for humankind. He offers a new perspective on how to lead nations and organizations to the future that has already become the present. Read more

This is an introductory text and laboratory manual to be used primarily in undergraduate courses. It is also useful for graduate students and research scientists who require an introduction to the theory and methods of nanopore sequencing. The book has clear explanations of the principles of this emerging technology, together with instructional material written by experts that describes how to use a MinION nanopore instrument for sequencing in research or the classroom.At Harvard University the book serves as a textbook and lab manual for a university laboratory course designed to intensify the intellectual experience of incoming undergraduates while exploring biology as a field of concentration. Nanopore sequencing is an ideal topic as a path to encourage students about the range of courses they will take in Biology by pre-emptively addressing the complaint about having to take a course in Physics or Maths while majoring in Biology. The book addresses this complaint by concretely demonstrating the range of topics — from electricity to biochemistry, protein structure, molecular engineering, and informatics — that a student will have to master in subsequent courses if he or she is to become a scientist who truly understands what his or her biology instrument is measuring when investigating biological phenomena. Read more

What is the mind? How did it evolve? Can we engineer it?This interdisciplinary short book explores the mind and its development from a computational perspective. It touches on its evolutionary development, its algorithmic nature and its scientific history by bridging ideas across Neuroscience, Computer Science, Biotechnology, Evolutionary History, Cognitive Science, Political Philosophy, and Artificial Intelligence.Never before had there been nearly as many scientists, resources or productive research focused on these topics, and humanity has achieved some understanding and some clarification. With the speed of progress it is timely to communicate an overreaching perspective, this book puts an emphasis on conveying the essential questions and what we know about their answers in a simple, clear and exciting way.Humans, along with the first RNA molecules, the first life forms, the first brains, the first conscious animals, the first societies and the first artificial agents constitute an amazing and crucial development in a path of increasingly complex computational intelligence. And yet, we occupy a minuscule time period in the history of Earth, a history that has been written by Genes, by Cultures and by Consciousnesses. If we abandon our anthropomorphic bias it becomes obvious that Humans are not so special after all. We are an important but short and transitory step among many others in a bigger story. The story of our computational minds, which is ours but not only ours.What is the relationship between computation, cognition and everything else? What is life and how did it originate? What is the role of culture in human minds?What do we know about the algorithmic nature of the mind, can we engineer it?What is the computational explanation of consciousness? What are some possible future steps in the evolution of minds?The underlying thread is the computational nature of the Mind which results from the mixture of Genes, Cultures and Consciousness. While these three interact in complex ways, they are ultimately computational systems on their own which appeared at different stages of history and which follow their own selective processes operating at different time scales. As technology progresses, the distinction between the three components materializes and will be a key determinant of the future.Among the many topics covered are the origin of life, the concept of computation and its relation to Turing Machines, cultural evolution and the notion of a Selfish Meme, free will and determinism, moral relativity, the hard problem of consciousness, the different theories of concepts from the perspective of cognitive science, the current status of AI and Machine Learning including the symbolic vs sub-symbolic dichotomy, the contrast between logical reasoning and neural networks, and the recent history of Deep Learning, Geoffrey Hinton, DeepMind and its algorithm AlphaGo. It also develops on the history of science and looks into the possible future building on the work of authors like Daniel Dennett, Yuval Harari, Richard Dawkins, Francis Crick, George Church, David Chalmers, Susan Carey, Stanislas Dehaene, Robert Boyd, Joseph Henrich, Daniel Kahneman, Moran Cerf, Josh Tenenbaum, David Deutsch, Steven Pinker, Ray Kurzweil, John von Neumann, Herbert Simon and many more. Andres Campero is a researcher and PhD student at the Brain and Cognitive Sciences Department and at the Computer Science and Artificial Intelligence Laboratory at the Massachusetts Institute of Technology (MIT). Read more

Microsoft Azure is a cloud computing platform that provides a wide variety of services that we can use without purchasing and arranging our hardware. It enables the fast development of solutions and provides the resources to complete tasks that may not be achievable in an on-premises environment. Azure Services like compute, storage, network, and application services allow us to put our effort into building great solutions without worrying about the assembly of physical infrastructure. This book covers the fundamentals of Azure, which will provide us the idea about all the Azure key services that we are most likely required to know to start developing solutions. After completing this book, we can crack job interviews or able to get different Microsoft Azure certifications. Microsoft Azure is a cloud service that can be used to for building, testing, and managing applications and services through a network of servers managed by Microsoft in various locations all over the world. Get the most out of Azure, simply by following the easy instructions fully explained in this audiobook. This step-by-step guide gives you everything you need to know to do more with Azure than you ever thought possible! Here is a preview of what you will learn in this guide: Infrastructure as a Service (IAAS) Platform as a Service (PAAS) Software as a Service (SAAS) Public, Private, and Hybrid Clouds Cloud Computing and Security Issues The Importance of Geopolitics in Cloud Computing Overview of Available Azure Services Development with Azure Mobile Services in Azure Azure Storage Services Data-Management Functions in Azure Messaging Functions on Microsoft Azure Azure's Content Delivery Network Developer Tools in Azure Application Management with Azure Machine Learning Capabilities in Azure Azure and the Internet of Things (IOT) Definition of Azure Devops Advantages of Azure Devops Privacy and Microsoft Azure Creating a Windows Virtual Machine Creating a Linux Virtual Machine And so much more! With this guide, you will learn everything you need to know about Microsoft Azure! Read more

Have you always wanted to Learn Python Programming but you have thought it to be too difficult for you?Are you a beginner or maybe you master other programming languages and you want to Learn Python Coding fast and efficiently?Are you looking for the best Python Crash Course?If yes, then this book is for you. You no longer have to lose your time and resources learning Python from long books, costly online courses, or very complicated Python tutorials.Are you ready to enter the exciting world of Python? Then this book is for you.Python is a programming language that has existed for over 20 years. The history of Python started in the late 1980s when its founder, Guido van Rossum, started working on it. The inspiration for Python programming came from the ABC programming language, whose first version was introduced in 1987. Guido van Rossum was one of the main implementers of the ABC programming language.After reading this book, you'll learn:- What is Python- How to install python and what is the best distribution- What are data types and variables- How to work with numbers in Python- What operators there are in Python and when to use them- How to manipulate Strings- How to implement Program Flow Controls- How to implement loops in Python- What are Python lists, tuples, sets, dictionaries, and how to use them- How to create modules and functions- How to program according to the Object-Oriented paradigm- How to create classes- What are and how to use Inheritance, Polymorphism and Abstraction and Encapsulationand much more... Read more

This Box Set Includes 3 Books: Python Programming For Beginners - Learn The Basics Of Python In 7 Days! Python Programming For Intermediates - Learn The Basics Of Python In 7 Days! Python Programming For Advanced - Learn The Basics Of Python In 7 Days! Python Programming For Beginners - Learn The Basics Of Python In 7 Days! Here's what you'll learn from this book: ✓Introduction ✓Understanding Python: A Detailed Background ✓How Python Works ✓Python Glossary ✓How to Download and Install Python ✓Python Programming 101: Interacting With Python in Different Ways ✓How to Write Your First Python Program ✓Variables, Strings, Lists, Tuples, Dictionaries ✓About User-Defined Functions ✓How to Write User-Defined Functions in Python ✓About Coding Style ✓Practice Projects: The Python Projects for Your Practice Python Programming For Intermediates - Learn The Basics Of Python In 7 Days! Here's what you'll learn from this book: ✓ Shallow copy and deep copy ✓ Objects and classes in Python–including python inheritance, multiple inheritances, and so on ✓ Recursion in Python ✓ Debugging and testing ✓ Fibonacci sequence (definition) and Memoization in Python in Python ✓ Arguments in Python ✓ Namespaces in Python and Python Modules ✓ Simple Python projects for Intermediates Python Programming For Advanced - Learn The Basics Of Python In 7 Days! Here's what you'll learn from this book: ✓File management ✓Python Iterator ✓Python Generator ✓Regular Expressions ✓Python Closure ✓Python Property ✓Python Assert, and ✓Simple recap projects Start Coding Now! Read more

This book is written for biologists, from undergraduate students to seasoned professionals, who wish to develop coding skills for the management, visualization and analysis of biological data. Coding and quantitative skills are critical for all areas of biological inquiry, yet many biology programs do not emphasize training in math, statistics, and computer science. This book tries to demystify coding, using a hands-on tutorial style without too much technical jargon. As such, it should be useful to current students, recent graduates, and working professionals who have not received formal training in computer science. Read more

Are you a self-taught data analyst who is looking to apply your newfound skills to practical data analysis tasks?Are you looking for a structured, practical, and hands-on approach to learning data analysis with Python?Want to become proficient in the Python libraries used by data analysts and scientists so you can build your portfolio of projects?If you answer yes to any of these questions, then "50 Days of Data Analysis with Python: The Ultimate Challenge Book for Beginners" is your perfect choice.For Data Analysts and Aspiring Data ScientistsThis book is perfect for beginners and aspiring data scientists alike. You'll not only conquer the basics but also dig deep into the functions most critical for data analysis. The aim of this book is to get you to a stage where you are comfortable jumping on any structured dataset and doing some analysis. This book bridges the gap between theory and practice, making it an ideal resource for those seeking to develop their data analysis skills.Are you ready to unlock the incredible power of Python for data analysis? Dive into the world of data with confidence in "50 Days of Data Analysis with Python."Learn by doing; Solve Real-world ProblemsThis book is all about learning by doing. You'll tackle real-world scenarios, roll up your sleeves, and get hands-on with data analysis. Here is what you are going to do:Explore real-world scenario simulations.Work with diverse datasets.Explore data cleaning and preprocessing.Extract insights from dataConduct statistical analyses.Create insightful visualizations.Train machine learning modelsExplore Key Python LibrariesIn this book, you will not only explore the main Python libraries used in data analysis, but you will also apply their numerous functions to real-world scenarios. Here is what you are going to practically learn:NumPy: Effortlessly handle numerical computations.pandas: Master data manipulation and analysis like a pro.Seaborn: Craft captivating visualizations.Matplotlib: Create stunning plots and charts.Scikit-learn (Sklearn): Embrace the world of machine learning.Unlock Python's Data Analysis CapabilitiesWith over 300 challenges, embark on an engaging 50-day journey to become a skilled data analyst with Python. Remember, success comes from embracing challenges, critical thinking, exploring different approaches, and unlocking your full potential.Start Your 50-Day Journey Today!Don't wait—make today Day 1 of your 50 Days to supercharge your data analysis proficiency. Get your copy now and seize the opportunity for growth and success! Read more

Suppose you are provided with a protein sequence and you know absolutely nothing about it. Now it’s your turn to gather information about that protein so that you can design experiments and bring the proteomics work forward. This book will teach you exactly how to deal with the protein sequence from the beginner’s level. I have written this book keeping some important points in my mind that I required when I was a beginner in Bioinformatics. This book is free of hustle bustle and I never focused on information. This book is for a layman who wants to study bioinformatics for him or herself. So use it as a bioinformatics practical hand book and develop your bioinformatics knowledge with it. However the theory part of bioinformatics is also required for the understanding of the practical so I am writing a basic beginner’s Bioinformatics theory eBook too. Hope to publish it soon. This book will teach you the following questions-How to find the desired protein sequence in NCBI and retrieve it in computer?How to run NCBI BLAST?How to search conserved domain in the database?How to perform multiple sequence alignments?How to construct a phylogenic tree from query sequences?How to predict secondary structure of a protein?How to gather information about a protein from PDB (protein data bank)?How to find known domains in your protein?How to find known motifs in your protein sequence?How to understand different chemical properties of a protein from its sequence?During the different chapters of the book I have mentioned the important topics to understand but there are many things that I have not mentioned about every database. You will find interesting to find those region on your own when you start to understand the system. You know basically Bioinformatics is an advanced database searching and we all search thousands of databases ourselves. So there is a database explorer somewhere in all of you. This book will increase the appetite of that explorer in you for sure. If it accomplishes that task, my efforts will pay off. Read more

A concise introduction to key computing skills for biologistsWhile biological data continues to grow exponentially in size and quality, many of today’s biologists are not trained adequately in the computing skills necessary for leveraging this information deluge. In Computing Skills for Biologists, Stefano Allesina and Madlen Wilmes present a valuable toolbox for the effective analysis of biological data.Based on the authors’ experiences teaching scientific computing at the University of Chicago, this textbook emphasizes the automation of repetitive tasks and the construction of pipelines for data organization, analysis, visualization, and publication. Stressing practice rather than theory, the book’s examples and exercises are drawn from actual biological data and solve cogent problems spanning the entire breadth of biological disciplines, including ecology, genetics, microbiology, and molecular biology. Beginners will benefit from the many examples explained step-by-step, while more seasoned researchers will learn how to combine tools to make biological data analysis robust and reproducible. The book uses free software and code that can be run on any platform.Computing Skills for Biologists is ideal for scientists wanting to improve their technical skills and instructors looking to teach the main computing tools essential for biology research in the twenty-first century.Excellent resource for acquiring comprehensive computing skillsBoth novice and experienced scientists will increase efficiency by building automated and reproducible pipelines for biological data analysisCode examples based on published data spanning the breadth of biological disciplinesDetailed solutions provided for exercises in each chapterExtensive companion website Read more

⭐ ⬇ DISCOVER HOW TO GET THE FREE BONUS OF 200+ PROMPTS ⬇ ⭐The Ultimate Guide to Using ChatGPT to Maximize Productivity and Significantly Boost Your Profits.ChatGPT is a language model developed by OpenAI that has revolutionized the way we interact with technology. It offers text comprehension, content generation of high quality, and new research frontiers, and has great potential to change the way we interact with technology.This guide will explain to you how to create compelling content with ease, from research to promotion to generating passive income streams that keep on giving with just minutes of effort.Using ChatGPT, you will be able to Impress your clients by completing their projects quickly and with high quality results, even if you have no previous experience, and you will free up your time to focus on what really matters.By reading this book you will discover:Introduction to ChatGPTBenefits of using ChatGPTGetting started with ChatGPTBest Practices for Using ChatGPT Effectively.Improve your productivity with ChatGPT: generate high-quality content in less time than you ever imagined possible.Utilize ChatGPT to make money and establish passive income streams that provide continuous returns.Quickly produce articles, emails, social media posts, books, videos and more200+ prompt templates for all situations that will allow you to use ChatGPT quickly and easily.Limitations of ChatGPTExclusive bonus: Gain access to a handpicked list of websites and services leveraging GPT4 to give you a head-start on utilizing this incredible technology.And Much more!✔ FREE BONUS - In addition to purchasing this book, you will receive a PDF download containing over 200 prompts for all situations, making it an excellent guide that will help you unlock and express the full potential of ChatGPT.If you're looking for an effective way to familiarize yourself with AI, this book is the best way to learn how to use CHATGPT.…What are you waiting for?Click the "BUY NOW" and Start your journey to financial freedom today! Read more

Drive development with automated tests and gain the confidence you need to write high-quality softwareKey FeaturesGet up and running with common design patterns and TDD best practicesLearn to apply the rhythms of TDD – arrange, act, assert and red, green, refactorUnderstand the challenges of implementing TDD in the Java ecosystem and build a planBook DescriptionTest-driven development enables developers to craft well-designed code and prevent defects. It's a simple yet powerful tool that helps you focus on your code design, while automatically checking that your code works correctly. Mastering TDD will enable you to effectively utilize design patterns and become a proficient software architect.The book begins by explaining the basics of good code and bad code, bursting common myths, and why Test-driven development is crucial. You'll then gradually move toward building a sample application using TDD, where you'll apply the two key rhythms -- red, green, refactor and arrange, act, assert. Next, you'll learn how to bring external systems such as databases under control by using dependency inversion and test doubles. As you advance, you'll delve into advanced design techniques such as SOLID patterns, refactoring, and hexagonal architecture. You'll also balance your use of fast, repeatable unit tests against integration tests using the test pyramid as a guide. The concluding chapters will show you how to implement TDD in real-world use cases and scenarios and develop a modern REST microservice backed by a Postgres database in Java 17.By the end of this book, you'll be thinking differently about how you design code for simplicity and how correctness can be baked in as you go.What you will learnDiscover how to write effective test cases in JavaExplore how TDD can be incorporated into crafting softwareFind out how to write reusable and robust code in JavaUncover common myths about TDD and understand its effectivenessUnderstand the accurate rhythm of implementing TDDGet to grips with the process of refactoring and see how it affects the TDD processWho this book is forThis book is for expert Java developers and software architects crafting high-quality software in Java. Test-Driven Development with Java can be picked up by anyone with a strong working experience in Java who is planning to use Test-driven development for their upcoming projects.Table of ContentsBuilding the Case for TDD Using TDD to Create Good CodeDispelling Common Myths about TDDBuilding a typical application using TDDWriting our First TestFollowing the Rhythms of TDDDriving Design: TDD and SOLIDTest Doubles: Stubs and MocksHexagonal Architecture: Decoupling external systemsFIRST Tests and the Test PyramidExploring TDD with Quality AssuranceTest First, Test Later, Test NeverDriving the domain layerDriving the database layerDriving the Web Layer Read more

This complete guide takes you on a tour of PowerShell from the basics to its advanced functionality, helping you automate your tedious and time-consuming system admin tasksKey FeaturesAutomate complex tasks, manipulate data, and secure your environmentWork with dual code for PowerShell 7 and Windows PowerShell to maintain compatibility with older versionsSee PowerShell in action, from learning the fundamentals to creating classes, scripts, and modulesBook DescriptionPowerShell scripts offer a convenient way to automate various tasks, but working with them can be daunting. Mastering PowerShell Scripting takes away the fear and helps you navigate through PowerShell's capabilities.This extensively revised edition includes new chapters on debugging and troubleshooting and creating GUIs (online chapter). Learn the new features of PowerShell 7.1 by working with parameters, objects, and .NET classes from within PowerShell 7.1.This comprehensive guide starts with the basics before moving on to advanced topics, including asynchronous processing, desired state configuration, using more complex scripts and filters, debugging issues, and error-handling techniques. Explore how to efficiently manage substantial amounts of data and interact with other services using PowerShell 7.1. This book will help you to make the most of PowerShell's automation features, using different methods to parse data, manipulate regular expressions, and work with Windows Management Instrumentation (WMI).What you will learnOptimize code with functions, switches, and looping structuresTest and debug your scripts as well as raising and catching errorsWork with objects and operators to test and manipulate dataParse and manipulate different data typesUse jobs, runspaces, and runspace pools to run code asynchronouslyWrite .NET classes with ease within PowerShellCreate and implement regular expressions in PowerShell scriptsMake use of advanced techniques to define and restrict the behavior of parametersWho this book is forThis book is for system administrators who want to automate and speed up their processes using PowerShell and Windows PowerShell. You'll need to know the basics of operating systems, but beginners with no prior experience with PowerShell will have no trouble following along.Table of ContentsIntroduction to PowerShellModules and Snap-InsWorking with Objects in PowerShellOperatorsVariables, Arrays, and HashtablesConditional Statements and LoopsWorking with .NETStrings, Numbers, and DatesRegular ExpressionsFiles, Folders, and the RegistryWindows Management InstrumentationWorking with HTML, XML, and JSONWeb Requests and Web ServicesRemoting and Remote ManagementAsynchronous ProcessingGraphical User InterfacesScripts, Functions, and Script BlocksParameters, Validation, and Dynamic ParametersClasses and EnumerationsBuilding ModulesTestingError HandlingDebugging and Troubleshooting Read more

Data science is a complex subject, but nevertheless one that can be made accessible to all through clear, intuitive explanations and worked examples. Existing software that forms the backbone of an immunologist's analytical toolkit (such as FlowJo and Prism) are expensive, inflexible and promotes a narrow mindset when it comes to analysing your data. On the other hand, the Python and R programming languages are open source, free and entirely customisable, giving the user the ability to implement any analysis they wish. ​ Although programming languages can seem daunting to the uninitiated, it's far easier to learn than many immunologists may think. Rather than seeking to become an expert programmer, an understanding of the main concepts is more than enough to conduct your own bespoke analyses when coupled with a sound mathematical and statistical understanding. ​ Our new book focusses on the practical aspects of data science, providing sufficient theoretical background without delving into all of the details of each of the methods presented. Introductory chapters are presented alongside the analysis of a publicly available data set, allowing the reader to have practical hands-on experience when learning about important concepts in statistics, machine learning and programming. Topics include: - ​​​ How to build a predictive model How to visualise high-dimensional data Basics of programming in Python and R What techniques exist to cluster data Which statistics test to use/why/when What is dimension reduction; when and how to use it ​ Once these fundamental topics have been covered, a number of case studies are presented, along with the underlying data, accompanying code and full explanations on topics such as automated, data-driven flow cytometry, building predictive models of disease using gene expression profiling and analysing high throughput sequencing data. Read more

Simplify your DevOps roles with DevOps tools and techniquesKey FeaturesLearn to utilize business resources effectively to increase productivity and collaborationLeverage the ultimate open source DevOps tools to achieve continuous integration and continuous delivery (CI/CD)Ensure faster time-to-market by reducing overall lead time and deployment downtimeBook DescriptionThe implementation of DevOps processes requires the efficient use of various tools, and the choice of these tools is crucial for the sustainability of projects and collaboration between development (Dev) and operations (Ops). This book presents the different patterns and tools that you can use to provision and configure an infrastructure in the cloud. You'll begin by understanding DevOps culture, the application of DevOps in cloud infrastructure, provisioning with Terraform, configuration with Ansible, and image building with Packer. You'll then be taken through source code versioning with Git and the construction of a DevOps CI/CD pipeline using Jenkins, GitLab CI, and Azure Pipelines. This DevOps handbook will also guide you in containerizing and deploying your applications with Docker and Kubernetes. You'll learn how to reduce deployment downtime with blue-green deployment and the feature flags technique, and study DevOps practices for open source projects. Finally, you'll grasp some best practices for reducing the overall application lead time to ensure faster time to market.By the end of this book, you'll have built a solid foundation in DevOps, and developed the skills necessary to enhance a traditional software delivery process using modern software delivery tools and techniquesWhat you will learnBecome well versed with DevOps culture and its practicesUse Terraform and Packer for cloud infrastructure provisioningImplement Ansible for infrastructure configurationUse basic Git commands and understand the Git flow processBuild a DevOps pipeline with Jenkins, Azure Pipelines, and GitLab CIContainerize your applications with Docker and KubernetesCheck application quality with SonarQube and PostmanProtect DevOps processes and applications using DevSecOps toolsWho this book is forIf you are a developer or a system administrator interested in understanding continuous integration, continuous delivery, and containerization with DevOps tools and techniques, this book is for you.Table of ContentsThe DevOps Culture and PracticesProvisioning Cloud Infrastructure with TerraformUsing Ansible for Configuring IaaS InfrastructureOptimizing Infrastructure Deployment with PackerManaging Your Source Code with GitContinuous Integration and Continuous DeliveryContainerizing Your Application with DockerManaging containers effectively with KubernetesTesting APIs with PostmanStatic Code Analysis with SonarQubeSecurity and Performance TestsSecurity in the DevOps Process with DevSecOpsReducing Deployment DowntimeDevOps for Open Source ProjectsDevOps Best Practices Read more

Build, deploy, test, and run cloud-native serverless applications using AWS Lambda and other popular AWS servicesKey FeaturesLearn how to write, run, and deploy serverless applications in Amazon Web ServicesMake the most of AWS Lambda functions to build scalable and cost-efficient systemsBuild and deploy serverless applications with Amazon API Gateway and AWS Lambda functionsBook DescriptionServerless computing is a way to run your code without having to provision or manage servers. Amazon Web Services provides serverless services that you can use to build and deploy cloud-native applications. Starting with the basics of AWS Lambda, this book takes you through combining Lambda with other services from AWS, such as Amazon API Gateway, Amazon DynamoDB, and Amazon Step Functions. You’ll learn how to write, run, and test Lambda functions using examples in Node.js, Java, Python, and C# before you move on to developing and deploying serverless APIs efficiently using the Serverless Framework. In the concluding chapters, you’ll discover tips and best practices for leveraging Serverless Framework to increase your development productivity. By the end of this book, you’ll have become well-versed in building, securing, and running serverless applications using Amazon API Gateway and AWS Lambda without having to manage any servers.What you will learnUnderstand the core concepts of serverless computing in AWSCreate your own AWS Lambda functions and build serverless APIs using Amazon API GatewayExplore best practices for developing serverless applications at scale using Serverless FrameworkDiscover the DevOps patterns in a modern CI/CD pipeline with AWS CodePipelineBuild serverless data processing jobs to extract, transform, and load dataEnforce resource tagging policies with continuous compliance and AWS ConfigCreate chatbots with natural language understanding to perform automated tasksWho this book is forThis AWS book is for cloud architects and developers who want to build and deploy serverless applications using AWS Lambda. A basic understanding of AWS is required to get the most out of this book.Table of ContentsThe evolution of ComputeEvent-driven ApplicationsThe FoundationsAdding Amazon API GatewayLeveraging AWS ServicesGoing Deeper with LambdaServerless FrameworkContinuous Integration/ Continuous Delivery with Serverless FrameworkData ProcessingAWS AutomationCreating ChatbotsSingle-page Web ApplicationsGraphQL APIs Read more

Learn the core concepts of geospatial data analysis for building actionable and insightful GIS applicationsKey FeaturesCreate GIS solutions using the new features introduced in Python 3.7Explore a range of GIS tools and libraries such as PostGIS, QGIS, and PROJLearn to automate geospatial analysis workflows using Python and JupyterBook DescriptionGeospatial analysis is used in almost every domain you can think of, including defense, farming, and even medicine. With this systematic guide, you'll get started with geographic information system (GIS) and remote sensing analysis using the latest features in Python.This book will take you through GIS techniques, geodatabases, geospatial raster data, and much more using the latest built-in tools and libraries in Python 3.7. You'll learn everything you need to know about using software packages or APIs and generic algorithms that can be used for different situations. Furthermore, you'll learn how to apply simple Python GIS geospatial processes to a variety of problems, and work with remote sensing data.By the end of the book, you'll be able to build a generic corporate system, which can be implemented in any organization to manage customer support requests and field support personnel.What you will learnAutomate geospatial analysis workflows using PythonCode the simplest possible GIS in just 60 lines of PythonCreate thematic maps with Python tools such as PyShp, OGR, and the Python Imaging LibraryUnderstand the different formats that geospatial data comes inProduce elevation contours using Python toolsCreate flood inundation modelsApply geospatial analysis to real-time data tracking and storm chasingWho this book is forThis book is for Python developers, researchers, or analysts who want to perform geospatial modeling and GIS analysis with Python. Basic knowledge of digital mapping and analysis using Python or other scripting languages will be helpful.Table of ContentsLearning about Geospatial Analysis with PythonLearning Geospatial DataThe Geospatial Technology LandscapeGeospatial Python ToolboxPython and Geographic Information SystemsPython and Remote SensingPython and Elevation DataAdvanced Geospatial Python ModelingReal-Time DataPutting It All Together Read more