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Do you need a website to support your freelance business or entrepreneurial venture? Or are you considering a career in web design? Maybe you're looking for your next career pivot, or you're simply seeking skills to give your CV that competitive edge?Wherever you are in your career, Confident Web Design can help. The ultimate beginner's guide to designing, building and publishing basic websites, this book features exclusive online exercises to help you practice your new skills in context. Covering the basics of HTML, CSS and JavaScript, as well as giving you a thorough grounding in the real-life application of these principles, this book provides helpful examples, explanations of technical terms, and clear, easy-to-understand language - meaning your first website is only a few chapters away.Taking you on a practical journey to publish a basic website from scratch, the book's structure is designed to break down each skill into manageable chunks. Wherever you are in your career, let Confident Web Design give you that cutting edge with vital programming and design skills.About the Confident series...From coding and web design to data, digital content and cyber security, the Confident books are the perfect beginner's resource for enhancing your professional life, whatever your career path.
An insightful journey to MLOps, DevOps, and Machine Learning in the real environment. Key Features - Extensive knowledge and concept explanation of Kubernetes components with examples. - An all-in-one knowledge guide to train and deploy ML pipelines using Docker and Kubernetes. - Includes numerous MLOps projects with access to proven frameworks and the use of deep learning concepts. Description 'Continuous Machine Learning with Kubeflow' introduces you to the modern machine learning infrastructure, which includes Kubernetes and the Kubeflow architecture. This book will explain the fundamentals of deploying various AI/ML use cases with TensorFlow training and serving with Kubernetes and how Kubernetes can help with specific projects from start to finish. This book will help demonstrate how to use Kubeflow components, deploy them in GCP, and serve them in production using real-time data prediction. With Kubeflow KFserving, we'll look at serving techniques, build a computer vision-based user interface in streamlit, and then deploy it to the Google cloud platforms, Kubernetes and Heroku. Next, we also explore how to build Explainable AI for determining fairness and biasness with a What-if tool. Backed with various use-cases, we will learn how to put machine learning into production, including training and serving. After reading this book, you will be able to build your ML projects in the cloud using Kubeflow and the latest technology. In addition, you will gain a solid knowledge of DevOps and MLOps, which will open doors to various job roles in companies. What you will learn - Get comfortable with the architecture and the orchestration of Kubernetes. - Learn to containerize and deploy from scratch using Docker and Google Cloud Platform. - Practice how to develop the Kubeflow Orchestrator pipeline for a TensorFlow model. - Create AWS SageMaker pipelines, right from training to deployment in production. - Build the TensorFlow Extended (TFX) pipeline for an NLP application using Tensorboard and TFMA. Who this book is for This book is for MLOps, DevOps, Machine Learning Engineers, and Data Scientists who want to continuously deploy machine learning pipelines and manage them at scale using Kubernetes. The readers should have a strong background in machine learning and some knowledge of Kubernetes is required. Table of Contents 1. Introduction to Kubeflow & Kubernetes Cloud Architecture 2. Developing Kubeflow Pipeline in GCP 3. Designing Computer Vision Model in Kubeflow 4. Building TFX Pipeline 5. ML Model Explainability & Interpretability 6. Building Weights & Biases Pipeline Development 7. Applied ML with AWS Sagemaker 8. Web App Development with Streamlit & Heroku
A book that will help you become the Mozart of Microservices Key Features - All codes tested on the latest software versions with visual illustrations. - Covers bleeding-edge DevOps skills to build a future-proof job profile. - Includes expert advice, industry insights, and logical analogies to craft a technical narrative. Description “Cracking Containers with Docker and Kubernetes” aims to be a comprehensive guide for learning and referencing all of the essential topics related to creating, managing, and running containers with Docker and Kubernetes. Students and professionals working on Containerized web applications can use this book to lay strong conceptual foundations and sharpen their skills. The first few chapters provide an overall picture of resource virtualization in computing and demonstrate the potential of containers. The intermediate chapters get to extensive detail about Docker and Kubernetes. You will gain in-demand skills such as Docker and Kubernetes CLI, as well as how to write Dockerfiles, Compose files, and Kubernetes YAML Manifests. Topics like Networking, Storage, Access Control, and Security are discussed with real-world implications. The final chapters move Kubernetes and Containers to the cloud while expanding their ecosystem with tools for Serverless deployment, logging and monitoring, CI/CD, and more for a highly available production-ready setup. After reading this book you will be able to plan your application’s migration to containers, prepare for Docker and Kubernetes Certifications, or apply for six digit DevOps jobs. What you will learn - Learn to create, manage and orchestrate Containers using Docker and Kubernetes. - Practice writing Dockerfiles, Compose Files and Kubernetes YAML Manifests. - Perform container networking, storage, authorization, security, and scaling in a production environment. - Explore shipping, CI/CD, Service Mesh, Logging & Monitoring in detail. - Get the Cracking Containers with Docker and Kubernetes know-how of hosted and Serverless Kubernetes on Cloud. Who this book is for This book is intended for students, enthusiasts, and professionals in Software Development, DevOps, and Cloud Computing who want to put their career progress on a pedestal by reducing the operational and scaling costs of their web applications and optimizing their IT infrastructure utilization. Table of Contents 1. Prologue to the Containers 2. Hello Containers! 3. Introduction to Docker 4. Writing Dockerfiles 5. Gearing up the toolbox! 6. Connectivity and Storage 7. Multi Container Applications with Docker Compose 8. Container Orchestration with Docker Swarm 9. Introduction to Kubernetes 10. Workload Orchestration with Kubernetes 11. Networking and Storage with Kubernetes 12. Advanced Orchestration with Kubernetes 13. Hosted Kubernetes on Cloud 14. Containers in Production with GKE 15. Serverless Containers 16. The Checkpoint
Exploring techniques and tools and best practices used in the real world. Key Features - Explore private and public key-based solutions and their applications in the real world. - Learn about security protocols implemented at various TCP/IP stack layers. - Insight on types of ciphers, their modes, and implementation issues.. Description Cryptography and Network Security teaches you everything about cryptography and how to make its best use for both, network and internet security. To begin with, you will learn to explore security goals, the architecture, its complete mechanisms, and the standard operational model. You will learn some of the most commonly used terminologies in cryptography such as substitution, and transposition. While you learn the key concepts, you will also explore the difference between symmetric and asymmetric ciphers, block and stream ciphers, and monoalphabetic and polyalphabetic ciphers. This book also focuses on digital signatures and digital signing methods, AES encryption processing, public key algorithms, and how to encrypt and generate MACs. You will also learn about the most important real-world protocol called Kerberos and see how public key certificates are deployed to solve public key-related problems. Real-world protocols such as PGP, SMIME, TLS, and IPsec Rand 802.11i are also covered in detail. What you will learn - Describe and show real-world connections of cryptography and applications of cryptography and secure hash functions. - How one can deploy User Authentication, Digital Signatures, and AES Encryption process. - How the real-world protocols operate in practice and their theoretical implications. - Describe different types of ciphers, exploit their modes for solving problems, and finding their implementation issues in system security. Who this book is for This book is for security professionals, network engineers, IT managers, students, and teachers who are interested in learning Cryptography and Network Security. Table of Contents 1. Network and information security overview 2. Introduction to cryptography 3. Block ciphers and attacks 4. Number Theory Fundamentals 5. Algebraic structures 6. Stream cipher modes 7. Secure hash functions 8. Message authentication using MAC 9. Authentication and message integrity using Digital Signatures 10. Advanced Encryption Standard 11. Pseudo-Random numbers 12. Public key algorithms and RSA 13. Other public-key algorithms 14. Key Management and Exchange 15. User authentication using Kerberos 16. User authentication using public key certificates 17. Email security 18. Transport layer security 19. IP security 20. Wireless security 21. System security About the Authors Prof. Bhushan Trivedi, Ph. D. is working as the Dean, Faculty of Computer Technology (FoCT) at the GLS University. He has two MOOCs, three international books, 100 odd research papers to his credit. He has conducted numerous workshops and seminar talks on pedagogy, research, online content preparation and management and various realms of security. Dr. Savita Gandhi is Dean, Faculty of Computer Science and IT at GLS University. Prior to holding her current position she was the Director of the School of Computer Science and headed the Dept. of Computer Science at Gujarat University. Dr Dhiren Pandit is working as an Assistant Professor in Mathematics at the Institute of Technology, Nirma University. He did his Doctorate from NIT Surat in the field of image processing and data mining. Due to his interdisciplinary work in the application of mathematics in computer science and experience, he is able to contribute to this project.
Techniques and Effective tips to get protected from Cyber Criminals Key Features - Learn to file a Cybercrime complaint. - Discover the New IT Rules 2021. - Understand the Artificial Intelligence (AI) in Cyber security. - Know how our online lives and real-world lives closely intertwined, each affecting the other. - Tips for protection of very young kids (5yr-8 yr), when online. - Identifying and keeping potential online predators and pedophiles at a distance.. Description Book is a step-by-step guide that handholds you through all the essential aspects of internet safety. The content is presented in a simple and easy-to-understand manner. True incidents, practical tips, survey results, conversation starters and teaching ideas given in the book, make the reading experience truly enriching. As per a recent survey amongst our volunteers, 94% said they were more vigilant and discerning towards misinformation primarily due to online safety they’d learned at Jaago Teens. They also felt that 70% of people were likely influenced by fake news during the Covid-19 pandemic. At the end of a Jaago Teens workshop, a teacher conceded. “Both, my daughter and I post a lot of pictures online. But, now I realize doing so can have dangerous consequences.” After a Corporate Jaago Teens Internet Safety workshop, a young 27-year old said, “Today we listened to many different aspects of Internet Safety. I think this was like a mock drill. If a situation arises where we need to apply what we have learned today, we will be able to do so!” What you will learn - Awareness of the IT Rules 2021. - Concept of plagiarism and copyright violation. - To modify the privacy settings on the social media platform, to ensure one’s safety. Who this book is for Children’s online life is different from those of grown-ups, if their online safety is a constant worry this book is a great resource to use. It tells you the kind of trouble children can get into when they are online, and suggests simple yet effective ways to deal with such situations. This book is a must-read for every parent, teacher or child who wants to avoid the temptations and perils of cyberspace. Table of Contents 1. An Introduction to Internet Safety 2. Real World and the Virtual World 3. Basic Do’s and Don’ts 4. Parental Control Options 5. Online Gaming 6. Recognizing Cyberbullying and Dealing with It 7. Privacy of Personal Information 8. Online Predators 9. Smartphone Safety, Your Phone Isn’t Smart, But You Are! 10. Modes of Digital Payments and Safe Online Payments 11. Reporting Cybercrime and Laws that protect against Online Harassment 12. Online Plagiarism 13. Privacy Settings for Various Online Platforms 14. A Downloadable JaagoTeens Presentation 15. Information Technology (Intermediary Guidelines and Digital Media Ethics Code) Rules 2021 16. Artificial Intelligence (AI) keeps you safe in the Real World and the Online World
Understand data in a simple way using a data lake. Key Features - In-depth practical demonstration of Hadoop/Yarn concepts with numerous examples. - Includes graphical illustrations and visual explanations for Hadoop commands and parameters. - Includes details of dimensional modeling and Data Vault modeling. - Includes details of how to create and define a structure to a data lake. Description The book 'Data Processing and Modeling with Hadoop' explains how a distributed system works and its benefits in the big data era in a straightforward and clear manner. After reading the book, you will be able to plan and organize projects involving a massive amount of data. The book describes the standards and technologies that aid in data management and compares them to other technology business standards. The reader receives practical guidance on how to segregate and separate data into zones, as well as how to develop a model that can aid in data evolution. It discusses security and the measures that are utilized to reduce the impact of security. Self-service analytics, Data Lake, Data Vault 2.0, and Data Mesh are discussed in the book. After reading this book, the reader will have a thorough understanding of how to structure a data lake, as well as the ability to plan, organize, and carry out the implementation of a data-driven business with full governance and security. What you will learn - Learn the basics of components to the Hadoop Ecosystem. - Understand the structure, files, and zones of a Data Lake. - Learn to implement the security part of the Hadoop Ecosystem. - Learn to work with the Data Vault 2.0 modeling. - Learn to develop a strategy to define good governance. - Learn new tools to work with Data and Big Data Who this book is for This book caters to big data developers, technical specialists, consultants, and students who want to build good proficiency in big data. Knowing basic SQL concepts, modeling, and development would be good, although not mandatory. Table of Contents 1. Understanding the Current Moment 2. Defining the Zones 3. The Importance of Modeling 4. Massive Parallel Processing 5. Doing ETL/ELT 6. A Little Governance 7. Talking About Security 8. What Are the Next Steps?
Data Science and Analytics explores the solutions to problems in society, environment and in industry. With the increase in the availability of data, analytics has now become a major element in both the top line and the bottom line of any organization. This book explores perspectives on how big data and business analytics are increasingly essential in better decision making. This edited work explores the application of big data and business analytics by academics, researchers, industrial experts, policy makers and practitioners, helping the reader to understand how big data can be efficiently utilized in better managerial applications. Data Science and Analytics brings together researchers, engineers and practitioners to encompass a wide and diverse range of topics in a wide range of fields. The book will provide unique insights to researchers, academics and data scientists from a variety of disciplines interested in analyzing and application of big data analytics, as well as data analysts, students and scholars pursuing advanced study in big data.
Discover one of the most complete dictionaries in data science. Key Features - Simplified understanding of complex concepts, terms, terminologies, and techniques. - Combined glossary of machine learning, mathematics, and statistics. - Chronologically arranged A-Z keywords with brief description. Description This pocket guide is a must for all data professionals in their day-to-day work processes. This book brings a comprehensive pack of glossaries of machine learning, deep learning, mathematics, and statistics. The extensive list of glossaries comprises concepts, processes, algorithms, data structures, techniques, and many more. Each of these terms is explained in the simplest words possible. This pocket guide will help you to stay up to date of the most essential terms and references used in the process of data analysis and machine learning. What you will learn - Get absolute clarity on every concept, process, and algorithm used in the process of data science operations. - Keep yourself technically strong and sound-minded during data science meetings. - Strengthen your knowledge in the field of Big data and business intelligence. Who this book is for This book is for data professionals, data scientists, students, or those who are new to the field who wish to stay on top of industry jargon and terminologies used in the field of data science. Table of Contents 1. Chapter one: A 2. Chapter two: B 3. Chapter three: C 4. Chapter four: D 5. Chapter five: E 6. Chapter six: F 7. Chapter seven: G 8. Chapter eight: H 9. Chapter nine: I 10. Chapter ten: J 11. Chapter 11: K 12. Chapter 12: L 13. Chapter 13: M 14. Chapter 14: N 15. Chapter 15: O 16. Chapter 16: P 17. Chapter 17: Q 18. Chapter 18: R 19. Chapter 19 : S 20. Chapter 20 : T 21. Chapter 21 : U 22. Chapter 22 : V 23. Chapter 23: W 24. Chapter 24: X 25. Chapter 25: Y 26. Chapter 26 : Z About the Authors Mohamed Sabri is the Director of Practice in Data Science and Artificial Intelligence in a business consulting firm. Thanks to his experience in the IT world, he is able to deliver end-to-end solutions in the field of AI. He is very strong in communication and well versed in technology popularization for complex projects. He has participated as a data scientist in several AI projects for large organizations such as banks and manufacturers. He has graduated in Economics and Mathematics from the University of Ottawa. Blog links: https://www.datalyticsbusiness.ca/ LinkedIn Profile: https://www.linkedin.com/in/mohamed-sabri/
Think about UIs using design thinking principles from an award winning graphic designer Key Features - Practical knowledge of visual design basics and typography. - Understand the modern UI to kick-start your career with UI designs. - Introduces you to explore UI designs for e-commerce web applications. Description From the initial introduction about the meaning behind interfaces to the technical skills of thinking and designing a modern UI, this book will guide you on designing the UI of a screen for a real-world application, infused with the newly learned knowledge with the Figma tool. You will be able to explore and practice visual design concepts, namely, color, contrast, balance, consistency, alignments, negative space, how to approach visual impairments, and many more. You will be able to learn about one of the most critical elements of how to think about a UI for which you will explore concepts such as memory, vision, processing of info and objects, models of thinking, and more. Furthermore, you will explore the Figma tool and a live practical example of how to design a UI for an e-commerce graphic application, including its shopping cart page and adding a payment method screen. What you will learn - Get familiar with the basic visual design concepts. - Understand the fundamentals of the User Interface and User Interaction. - An overview of Search Results, Font Psychology, and Typography. - Learn to work with some common interface elements. - Understand how real-time collaborative editing works in the Figma UI design tool. Who this book is for This book is literally for everyone! You should only be loaded with plenty of curiosity. No previous knowledge of the field is required. Table of Contents 1. Definition of the User Interface 2. The Web and Graphic User Interfaces 3. Explanation to Typography 4. Visual Design Basics 5. Thinking About User Interaction 6. Usability 7. Know Your Habits 8. Interfaces’ Elements 9. Foreword to an E-commerce 10. A Small Introduction to Figma 11. Building a Shopping Cart 12. Farewell and Future Considerations About the Authors Dario Calonaci is a published author and an award-winning graphic designer. After completing his Art Diploma under the Renaissance classics, he worked with brands like The Ritz-Carlton, Designers for Obama, Rio+20 (United Nations conference), and Fortune 500 companies. His art has been published worldwide in a plethora of books, plus exhibitions from Rome to New York. LinkedIn Profile: https://www.linkedin.com/in/dariocalonaci/ Blogs: www.dariocalonaci.com
Conceptualizing deep learning in computer vision applications using PyTorch and Python libraries. Key Features - Covers a variety of computer vision projects, including face recognition and object recognition such as Yolo, Faster R-CNN. - Includes graphical representations and illustrations of neural networks and teaches how to program them. - Includes deep learning techniques and architectures introduced by Microsoft, Google, and the University of Oxford. Description Elements of Deep Learning for Computer Vision gives a thorough understanding of deep learning and provides highly accurate computer vision solutions while using libraries like PyTorch. This book introduces you to Deep Learning and explains all the concepts required to understand the basic working, development, and tuning of a neural network using Pytorch. The book then addresses the field of computer vision using two libraries, including the Python wrapper/version of OpenCV and PIL. After establishing and understanding both the primary concepts, the book addresses them together by explaining Convolutional Neural Networks(CNNs). CNNs are further elaborated using top industry standards and research to explain how they provide complicated Object Detection in images and videos, while also explaining their evaluation. Towards the end, the book explains how to develop a fully functional object detection model, including its deployment over APIs. By the end of this book, you are well-equipped with the role of deep learning in the field of computer vision along with a guided process to design deep learning solutions. What you will learn - Get to know the mechanism of deep learning and how neural networks operate. - Learn to develop a highly accurate neural network model. - Access to rich Python libraries to address computer vision challenges. - Build deep learning models using PyTorch and learn how to deploy using the API. - Learn to develop Object Detection and Face Recognition models along with their deployment. Who this book is for This book is for the readers who aspire to gain a strong fundamental understanding of how to infuse deep learning into computer vision and image processing applications. Readers are expected to have intermediate Python skills. No previous knowledge of PyTorch and Computer Vision is required. Table of Contents 1. An Introduction to Deep Learning 2. Supervised Learning 3. Gradient Descent 4. OpenCV with Python 5. Python Imaging Library and Pillow 6. Introduction to Convolutional Neural Networks 7. GoogLeNet, VGGNet, and ResNet 8. Understanding Object Detection 9. Popular Algorithms for Object Detection 10. Faster RCNN with PyTorch and YoloV4 with Darknet 11. Comparing Algorithms and API Deployment with Flask 12. Applications in Real World About the Authors Bharat Sikka is a data scientist based in Mumbai, India. Over the years, he has worked on implementing algorithms like YOLOv3/v4, Faster-RCNN, Mask-RCNN, among others. He is currently working as a data scientist at the State Bank of India. He also has a thorough knowledge and understanding of various programming languages such as Python, R, MATLAB, and Octave for Machine Learning, Deep Learning, Data Visualization and Analysis in Python, R, and Power BI, Tableau. He holds an MS degree in Data Science and Analytics from Royal Holloway, University of London, and a BTech degree in Information Technology from Symbiosis International University and has earned multiple certifications, including MOOCs in varied fields, including machine learning. He is a science fiction fanatic, loves to travel, and is a great cook. Blog links: https://github.com/bharatsikka LinkedIn Profile: www.linkedin.com/in/bharat-sikka