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Get hands-on training on any web crawling/scraping tool and uses of web scraping in the real-time industry Key Features -Includes numerous use-cases on the use of web scraping for industrial applications. -Learn how to automate web scraping tasks. -Explore ready-made syntaxes of Python scripts to run web scraping. Description A Python Guide for Web Scraping is a book that will give information about the importance of web scraping using Python. It includes real-time examples of web scraping. It implies the automation use cases of web scraping as well. It gives information about the different tools and libraries of web scraping so that readers get a wide idea about the features and existence of web scraping. In this book, we started with the basics of Python and its syntactical information. We briefed about the use cases and features of Python. We have explained the importance of Python in automation systems. Furthermore, we have added information about real-time industrial examples. We have concentrated and deep-dived into Python’s importance in web scraping, explained the different tools and their usages. We have explained the real-time industrial domain-wise use cases for web scraping. What you will learn -Explore the Python syntax and key features of using Python for web scraping. -Usage of Python in the web scraping tasks and how to automate scraping. -How to use different libraries and modules of Python. Who this book is for This book is basically for data engineers and data programmers who have a basic knowledge of Python and for the readers who want to learn about web scraping projects for industries. Table of Contents 1. Python Basics 2. Use Cases of Python 3. Automation Using Python 4. Industrial Automation-Python 5. Web Scraping 6. Web Scraping and Necessity 7. Python - Web Scraping and Different Tools 8. Automation in Web Scraping 9. Use Cases-Web Scraping 10. Industrial Benefits of Web Scraping About the Authors Mr Pradumna Panditrao is currently working as a Senior Software Engineer and a DevOps tool developer. He has done his Masters in networking and telecommunications. He has a total of 8+ years of experience in various domains like Software Development, DevOps Automation tools, Data mining Crawling tools, Cloud Technologies, and Hardware Profiling. He has good exposure to the cloud and has published a paper on Cognitive Radio, 4G Technology Algorithms. He has given embedded software development lectures and lab demo sessions at Bits Pilani, Goa in 2014-2015.
Real User Monitoring, Application Performance Monitoring, Alerting, and Dashboarding Using Elastic Stack Key Features -Numerous examples and visual representations of Elastic APM's capabilities. -Covers Elastic APM cloud deployment, Kubernetes clusters, and real-user monitoring. -Includes Kibana's visualization, Alerting and Dashboarding features. Description This book teaches an APM engineer how to monitor software services and applications in real time, including collecting detailed performance data on the response time for incoming requests, database queries, cache calls, and external HTTP requests. The book helps readers to explore the architecture and components of the Elastic APM stack. It also teaches you how to architect, deploy, and configure the Elastic APM stack to meet your specific requirements. The book focuses on monitoring and observability for applications and infrastructures built with Containers and Kubernetes. The book helps you configure APM capabilities like synthetic transaction and real-user transaction monitoring, integration with open-source tools like Prometheus, and data collection and processing using Logstash. Additionally, the book discusses how to use the Kibana dashboard features provided by Elastic APM in conjunction with alerting and dashboards to analyze the application's performance. Finally, the book teaches Site Reliability Engineers (SREs) how to meet service-level objectives through indicators such as availability, latency, quality, and saturation. What you will learn -Unleash the need and the applications of observability. -Learn to architect and deploy the Elastic APM stack. -Practice observability of monolithic and microservices-based applications. -Learn advanced observability of Containers and Kubernetes cluster infrastructure. -Uncover insights on user experience, uptime, and synthetic monitoring. -Learn to use Kibana for exploiting alerts and visualization features. Who this book is for Professionals in the fields of Application Performance Monitoring, Observability, Site Reliability Engineering, Software Development, AIOPS, and Cloud and Data Center Architecture will benefit greatly from this book. It would be beneficial, but not necessary, to have some knowledge of programming. Table of Contents 1. Introduction to Application Observability 2. Elastic Observability Features 3. Elastic Observability Deployment Architecture 4. Deployment of the Elastic Observability Platform 5. Use Case. Observability for a Containerized Java Application 6. Use Case. Observability for a Kubernetes-based Application 7. Observability for a .Net Core Application 8. Elastic Observability. User Experience, Uptime, and Synthetic Monitoring 9. Logstash Pipelines in Elastic Observability 10. Prometheus Integration with the Elastic Observability Platform 11. Machine Learning, Alerting, and Dashboards
Explore Machine Learning Techniques, Different Predictive Models, and its Applications Key Features -Extensive coverage of real examples on implementation and working of ML models. -Includes different strategies used in Machine Learning by leading data scientists. -Focuses on Machine Learning concepts and their evolution to algorithms. Description This book covers basic concepts of Machine Learning, various learning paradigms, different architectures and algorithms used in these paradigms. You will learn the power of ML models by exploring different predictive modeling techniques such as Regression, Clustering, and Classification. You will also get hands-on experience on methods and techniques such as Overfitting, Underfitting, Random Forest, Decision Trees, PCA, and Support Vector Machines. In this book real life examples with fully working of Python implementations are discussed in detail. At the end of the book you will learn about the unsupervised learning covering Hierarchical Clustering, K-means Clustering, Dimensionality Reduction, Anomaly detection, Principal Component Analysis. What you will learn -Learn to perform data engineering and analysis. -Build prototype ML models and production ML models from scratch. -Develop strong proficiency in using scikit-learn and Python. -Get hands-on experience with Random Forest, Logistic Regression, SVM, PCA, and Neural Networks. Who this book is for This book is meant for beginners who want to gain knowledge about Machine Learning in detail. This book can also be used by Machine Learning users for a quick reference for fundamentals in Machine Learning. Readers should have basic knowledge of Python and Scikit-Learn before reading the book. Table of Contents 1. Introduction to Machine Learning 2. Linear Regression 3. Classification Using Logistic Regression 4. Overfitting and Regularization 5. Feasibility of Learning 6. Support Vector Machine 7. Neural Network 8. Decision Trees 9. Unsupervised Learning 10. Theory of Generalization 11. Bias and Fairness in ML About the Authors Dr Deepti Chopra is working as an Assistant Professor (IT) at Lal Bahadur Shastri Institute of Management, Delhi. She has around 7 years of teaching experience. Her areas of interest include Natural Language Processing, Computational Linguistics, and Artificial Intelligence. She is the author of three books and has written several research papers in various international conferences and journals.
Deploy serverless and scalable cloud-native applications with Jakarta EE Key Features -Example-driven approach crafted specially for developers and architects. -Covers all core areas for cloud-native development. -Step-by-step implementation of core concepts, including application scalability and security, serverless, and containerization. Description The book helps readers to get a basic understanding of features provided by the cloud and core concepts of cloud native development. A hands-on approach makes sure that after reading the book, one can straight away implement the concepts in their daily design and development activities. The book starts with the basics of cloud computing and moves on to understanding the core concepts to create a production-ready cloud-native application. The book helps readers to develop a code that is testable and maintainable to support Agile cloud native development. This book also talks about the security and scalability aspects of applications which are the backbone of any large-scale application. The book covers advanced cloud native application development approaches using containers and serverless approaches. The book will help readers to get ready for a cloud native development journey. Whether one is creating a small application or a large scale application, core concepts explained in this book remain relevant and will work as a guiding light for developers and architects. What you will learn -Explains the core features that are part of cloud computing. -Build applications that are fast to market due to testability and maintainability. -Build applications that are secured against vulnerabilities. -Build applications that are easy to scale. Who this book is for The book is meant for software developers, architects and technical readers who want to learn about Cloud-based application development. Basic knowledge of the Java programming language or Jakarta EE platform is expected to understand code examples used in the book. Table of Contents 1. Introduction to Cloud Computing 2. Design for Cloud 3. Major Players in Cloud Computing 4. Sample Application Using Jakarta EE 5. Testing Cloud-Native Applications 6. Continuous Integration and Continuous Delivery 7. Securing Cloud-Based Applications 8. Scalability 9. Monitoring, Alerting, and Reporting 10. Containers 11. Serverless Computing 12. Best Practices for Developing Cloud-Native Applications About the Authors Kamalmeet Singh, has 16 years of experience in the IT Industry. He has worked in bootstrapping startups as well as Fortune 500 companies. He has worked in different technologies and domains. The technologies he has worked on range from Cloud computing, Machine Learning, Augmented reality, Serverless applications, Microservices, Mobile applications, Java, Python, ROR, C#, and so on. He has co-authored two books on Java design patterns and microservices. He is passionate about cloud computing and exploring the power of the LinkedIn profile: https://www.linkedin.com/in/meenukohli78/
Learn how to work towards making the most out of a career in emerging tech Key Features Understand the core concepts related to careers in emerging tech. Learn innovative, exclusive, and exciting ways to design a successful career in ET. Reduce your learning curve by examining the career trajectories of eminent ET professionals. Ways to evolve and adapt to changing ET paradigms. Practical perspective from the field. Description Cracking the emerging tech code will help you attain your Emerging Technology (ET) career goals faster without spending years in committing avoidable mistakes, recovering from them, and learning things the hard way. You can apply practical tips in areas such as improving your ability to craft market-friendly use cases and evolving a solution approach in new and diverse tech or business environments, to propel forward your career in strategic and proactive ways. It outlines ways in which you can explore and capitalize on hidden opportunities while working on important career aspects. The anecdotes and solutions provided will aid you in getting an inside out view to reduce your learning curve. This book will help you in gaining both magnitude and direction in your ET career journey and prevent you from getting overwhelmed or pinned down by the forces of ET. Authored by an ET professional, this book will take you through a series of steps to deepen your understanding of the forces that shape one’s ET career and successfully dealing with them. It also helps bust myths, addresses fallacies, and common misconceptions that could harm one’s career prospects. There are also practical and easy-to-adopt tips, methods, tracking mechanisms, and information that will improve career standing and professional growth. This book makes it easy for you to enhance your employability and job market relevance so that you can sprint towards a rewarding career. What will you learn Through this book, you will connect with ways and means to build a strong and rewarding emerging tech career. You will be able to work on identifying the right technology and employer, enhancing employability and differentiation in the job market, addressing challenges and connecting with enablers, accurate growth strategies and execution principles. Who this book is for This book is for current and aspiring emerging tech professionals, students, and anyone who wishes to understand ways to have a fulfilling career in emerging technologies such as AI, blockchain, cybersecurity, IoT, space tech, and more. Table of Contents 1. Introduction 2. The best ET for me and some myth bursting 3. Getting prepared and charting a roadmap 4. Identifying the requirements and getting help 5. Dealing with headwinds and drawing a career change action plan 6. Building an ET friendly résumé and finding the right employer 7. Getting hired through social media 8. Job search 9. Impressing the emerging tech jury 10. The secret sauce 11. Becoming a thought leader 12. Measuring success and making course corrections 13. Drawing the two-year plan 14. Building your leadership capabilities 15. To start-up or not? 16. Communications skills: getting it right 17. Building a personal brand 18. Post-script About the Authors Prayukth has been actively involved in productizing and promoting cross eco-system collaboration in the IoT space for over half-a-decade. In recent years, he has focused on exposing APT groups, global footprint, and in evaluating the evolving threat landscape surrounding IoT and OT environments. In his current role, he has taken Subex’s IoT business to new geographies. Your Linkedin profile: https://www.linkedin.com/in/prayukthkv/
Build robust and secure applications using the building blocks of Docker Key Features Understand the fundamentals of Containers. Understand the working of the entire Docker ecosystem. Learn how to utilize Docker Networking capabilities to its fullest. Learn how to secure Docker Containers. Get familiar and work with Docker Enterprise Edition. Description The book starts by introducing Containers and explains how they are different from virtual machines, and why they are the preferred tool for developing applications. You will understand the working of Images, Containers, and their associated Storage and will see how all the moving parts bind together to work synchronously. The book will then focus on Docker Swarm, the mechanism for orchestrating several running Docker containers. It then delves deeper into Docker Networking. Towards the end, you will learn how to secure your applications, especially by leveraging the native features of Docker Enterprise Edition. What will you learn Learn how to use Docker Images. Get to know more about Docker Storage. Learn how to use Volume plugins in Docker services. Learn how to deploy a service to the Swarm. Learn how to manage, scale, and maintain containerized applications. Who this book is for This book is for anyone who is looking to learn Docker. It is also useful for professionals who are looking to build and deploy web apps using Docker. Table of Contents 1. Introduction to Containerization and Docker 2. Containers and Images 3. Storage Drivers and Volumes 4. The Container Network Model and the Docker Bridge 5. Docker Swarm 6. Docker Networking 7. Docker Security-1 8. Docker Security-II About the Authors Saibal Ghosh has spent a substantial part of his career working with databases. However, in the last few years, he gravitated towards the cloud, cloud security, and newer technologies like Docker and Kubernetes. He has developed a deep understanding of these concepts and technologies bolstered by the insight gained from many years of experience working with applications, databases, storage and infrastructure, and the understanding of how data is stored, moved, and secured. He currently works as a Principal Architect in Ericsson India Ltd. and spends a substantial amount of time playing around with Docker and Kubernetes. He holds numerous certifications around applications, databases, cloud, and cloud security and is also a member of Leader’s Excellence, Harvard Square. Your LinkedIn Profile: https://www.linkedin.com/in/saibal-ghosh-mle%E2%84%A0-ccsk-prince2-%C2%AE-469b0a7/
State-of-the-art BERT implementation for text classification Description This book provides a solid foundation for ‘Natural Language Processing’ with pragmatic explanation and implementation of a wide variety of industry wide scenarios. After reading this book, one can simply jump to solve real world problems and join the league of NLP developers. It starts with the introduction of Natural Language Processing and provides a good explanation of different practical situations which are currently implemented across the globe. Thereafter, it takes a deep dive into the text classification with different types of algorithms to implement the same. Then, it further introduces the second important NLP use case called Named Entity Recognition with its popular algorithm choices. Thereafter, it provides an introduction to a state of the art language model called BERT and its application. What you will learn -Learn to implement transfer learning on pre-trained BERT models. -Learn to demonstrate a production ready Text Classification for domain specific data and networking using Python 3.x. -Learn about the domain specific pre trained models with a library called `aiops` which has been specially designed for this book. Who this book is for This book is meant for Data Scientists and Machine Learning Engineers who are new to Natural Language Processing and want to quickly implement different NLP use-cases. Readers should have a basic knowledge of Python before reading the book. Table of Contents 1. Introduction to NLP and Different Use-Cases 2. Deep Dive into Text Classification and Different Types of Algorithms in Industry 3. Named Entity Recognition 4. BERT and its Application 5. BERT: Text Classification 6. BERT: Text Classification Code About the Authors Amandeep has been working as a technical lead in the field of software development at the time of publishing this book. He has worked for almost eight years in a few of the top MNCs.
A step-by-step guide that will help you manage data in a relational database using SQL with ease Key Features Understand the concepts related to relational databases. Learn how to install MariaDB and MySQL on Windows, Linux and tools to access it. Learn how to connect Python and Pandas to MySQL/MariaDB. Description This book starts with the concepts in RDBMS (Relational Database Management Systems) and SQL (Structured Query Language). The first few chapters cover the definitions and a brief explanation of all the important concepts. They also cover the installation of MariaDB and MySQL on Windows and Raspberry Pi, as well as the setup of various tools used to connect to MySQL and MariaDB server processes. We will also understand how to install sample schemas and how to use basic SQL queries. Then we move on to the SELECT query in detail. The book explores the data retrieval aspect of SQL queries in detail with the WHERE clause and NULL handling in detail. The book also explores the functions available in MySQL. Those are single row and group functions. Then we explore how to combine the data from multiple sources. The technique is known as Joins, and we will learn ANSI style and the old-style syntax for all the types of Joins. The last part explores the DDL and DMLs in depth. We also learn the concepts of Transactions and Constraints. The book explores how we can run the SQL queries from a Python 3 program and load a pandas DataFrame with the data from a table in a schema in the MySQL database. What will you learn Understand the basics of MySQL and MariaDB. Get familiar with MySQL Arithmetic Operators, DDL, DML, DCL & TCL commands. Understand the concept of Single-Row Functions and Group Functions in detail. Retrieve data from multiple sources using the Joins. Who this book is for This book is designed for beginners as well as professionals alike. The book will also be useful to Data Scientists, Data Analysts, Database Administrators, and Data Engineers. Table of Contents 1. Introduction and Installation 2. Getting Started with MySQL 3. Getting Started with SQL Queries 4. The WHERE clause in detail 5. Single Row Functions 6. Group Functions 7. Joins in MySQL 8. Subqueries 9. DDL, DML, and Transactions 10. Views 11. Python 3, MySQL, and Pandas About the Author Ashwin is an experienced veteran who, for the past 25 years, has been working with STEM (Science, Technology, Engineering, and Mathematics). In his career, Ashwin has worked for more than 7 years as an employee for various IT companies and Software Product Companies. He has written more than 2 dozen books on Arduino, Python programming, Computer Vision, IoT, databases, and other popular topics with BPB and other international publications. He has also reviewed many other technical books. He also creates courses for BPB and other platforms and teaches to 60000 students online. He has been working as a freelancer since 2017. He got his first taste in writing in 2015 when he wrote his first book on Raspberry Pi. In his free time, Ashwin makes videos for his Youtube channel, which has 10000 subscribers now. Outside work, Ashwin volunteers his spare time as a STEM Ambassador, helping, coaching, and mentoring young people in taking up careers in technology. Your Blog links: https://www.youtube.com/ashwinpajankar Your LinkedIn Profile: https://www.linkedin.com/in/ashwinpajankar/
Concise Interpretation of every essential element of Python with Use-cases Key Features -Numerous examples and solutions to assist beginners in understanding the concept. -Contains visual representations of data structures. -Demonstrations of how to use data structures with a Python implementation. Description This book will aid you in your learning of the Python 3.x programming language. The chapters in this book will benefit every aspect of a programmer's or developer's life by preparing them to solve problems using Python programming and its key data structures and internals. This book explains the built-in and user-defined data structures in Python 3.x. The book begins by introducing Python, its fundamental data structures, and asymptotic notations. Once you master the fundamentals of Python, you'll be able to fully comprehend the built-in data structures. The book covers real-world applications to understand user-defined data structures and their actual implementation. Towards the end, it will help you investigate how to solve practical problems by first comprehending the issue at hand. After reading this book, you will be able to identify data structures and utilize them to solve a specific problem. You will learn about various algorithm implementations in Python and use this knowledge to advance your Python skills. 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 -Calculate the complexity of time and space using asymptotic notations. -Discover Python 3.x's built-in and user-defined data structures. -Create user-defined data structures from the bottom up. -Make use of libraries to create new user-defined data structures. -Determine and implement the most appropriate data structure for resolving issues. Who this book is for This book caters to those who want to enhance their careers as application developers, machine learning engineers, or researchers. Knowing basic programming concepts will be good, but not mandatory. Table of Contents 1. Python 2. Data Types 3. Algorithm Analysis 4. Data Structure Introduction 5. List 6. Dictionary 7. Tuple 8. Sets 9. Arrays 10. Stack 11. Queue 12. Trees 13. Linked Lists 14. Graphs 15. HashMaps 16. Practical Problem Solutions
A refresher for Java developers on how to use Selenium IDE and Selenium Grid to automate web browsers Key Features -Extensive practical demonstration of Selenium with numerous real-world examples. -Includes thorough examination of various test automation ideas. -Covers tools in conjunction with Selenium for implementing browser and web test automation projects. Description This book introduces setting up the environment for writing test scripts after covering Selenium and its capabilities. Numerous functionalities, including the web driver interface, the web element interface, and locators, are illustrated in-depth using the By class. Additionally, the book presents tasks such as HTML element manipulation, mouse and keyboard operations, dropdown, table, window, alert, frame, action class, and synchronization. Along with Selenium IDE and Selenium Webdriver, the book also covers another critical feature, which is the implementation of Selenium Grid, that allows the test suite to execute in parallel across several settings. Several add-on automation scripts, such as those for taking screenshots, object and data information, are thoroughly displayed and explained in this book. The book discusses tools like TestNG and Maven that aid in the overall development of the test project ecosystem. After reading the book, you should feel extremely competent in utilizing Selenium to automate a variety of web and browser testing scenarios and tasks. What you will learn -Get trained to automate the end-to-end testing of online applications with Selenium Webdriver. -Confidently configure the Selenium Grid for cross-browser testing. -Create locators quickly for various HTML elements on the page. -Opportunities to improve test writing skills with the popular unit test framework, TestNG. -An in-depth explanation of the management of objects and data in the test project. Who this book is for This book is intended for software test engineers who wish to develop a strong foundation in Selenium implementation to create test automation solutions. Basic knowledge of testing and Java as a programming language is required. Table of Contents 1. Introduction to Selenium 2. Preparing System and Application Under Test 3. WebDriver, WebElement, and By 4. Concept of Synchronization 5. Working with Web Elements—Form, Table, and Dropdown 6. Working with Web Element—Alert, Frame, IFrame, and Window 7. Extra Concepts – Action, Screenshot, WebDriverManager 8. What is TestNG 9. Concept of Page Object Model 10. Data Driving Test 11. Introducing Maven 12. Selenium Grid