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DESCRIPTIONFlutter Handbook is the t to becoming a proficient Flutter app developer, catering to all levels, from beginners to experts. This comprehensive guide takes you by the hand, providing step-by-step instructions on every aspect of Flutter app development. Starting from the basics, you'll learn how to install and run Flutter, as well as core concepts such as widgets, state management, and navigation. As you progress, the book delves deep into advanced topics, such as implementing CRUD (Create, Read, Update, Delete) functions using Firebase Firestore. Flutter Handbook is more than just a tutorial book. It also provides invaluable tips, tricks, and small tasks at the end of each chapter to reinforce your understanding and equip you with real-world skills. By the end of this journey, you'll have the expertise to release your Flutter app to the Play Store or App Store with confidence.TABLE OF CONTENTS 1. Introduction to Flutter2. Getting Started3. Widgets Widgets Widgets!4. Stateful and Stateless Widgets5. Navigation and Routing6. Firebase Firestore with Flutter7. Futures, Awaits, and Async8. Persistence and Data Modeling9. Deploying

Empowering You to Master Business Intelligence and Solve Real-world Analytical Problems.DESCRIPTIONIn today's analytics landscape, proficiency in Excel and Power BI is practically a prerequisite for a successful career. This book provides a concise yet comprehensive exploration of these foundational elements of modern Business Intelligence (BI).Comprising ten chapters, this book covers the entire development journey of a Power BI analytical solution, spanning from data modeling and preparation to report creation, publication, and dashboard and app deployment. It offers insights into security measures and performance optimization, ensuring a well-rounded understanding of the BI ecosystem. Furthermore, it delves into advanced topics, such as leveraging data science algorithms within reports, offering readers an extensive learning experience. The book takes a holistic approach to these technologies, offering a contrast to the narrow perspectives often adopted by contemporary BI professionals who rely solely on a single tool or language. The book allows data enrichment through calculations that can be achieved using various languages, including SQL queries at the source, Power Query Formula Language, M, Python, R, and DAX. By the end of this book you will master these options but be able to also weigh their pros and cons to make informed decisions.TABLE OF CONTENTS 1. Introducing the Theoretical Background for Democratizing Analytics2. Acquiring and transforming data from multiple sources3. Power Query Transformations and Formula Language (M) Overview4. Building a simple analytical solution with Power Pivot in Excel5. Enhancing the model and business analysis with DAX6. Creating reports in Power BI Desktop7. Using the Power BI Service8. Data Science in Power BI 9. Optimizing Power BI models and reports10. Deploying, Maintaining and Securing Power BI Assets Index

DESCRIPTIONAre you looking to unlock the transformative potential of data analytics in the dynamic world of Banking, Financial Services, and Insurance (BFSI)? This book is your essential guide to mastering the intricate interplay of data science and analytics that underpins the BFSI landscape.Designed for intermediate-level practitioners, as well as those aspiring to join the ranks of BFSI analytics professionals, this book is your compass in the data-driven realm of banking. Address the unique challenges and opportunities of the BFSI sector using Artificial Intelligence and Machine Learning models for a data-driven analysis.¿¿¿¿TABLE OF CONTENTS 1. Introduction to BFSI and Data-Driven Banking 2. Introduction to Analytics and Data Science 3. Major Areas of Analytics Utilization4. Understanding Infrastructures behind BFSI for Analytics5. Data Governance and AI/ML Model Governance in BFSI 6. Domains of BFSI and team planning 7. Customer Demographic Analysis and Customer Segmentation 8. Text Mining and Social Media Analytics 9. Lead Generation Through Analytical Reasoning and Machine Learning10. Cross Sell and Up Sell of Products through Machine Learning11. Pricing Optimization12. Data Envelopment Analysis 13. ATM Cash Forecasting14. Unstructured Data Analytics 15. Fraud Modelling 16. Detection of Money Laundering and Analysis 17. Credit Risk and Stressed Assets 18. High Performance Architectures: On-Premises and Cloud 19. Growing Trends in the Data-Driven Future of BFSI

DESCRIPTIONThis book is an in-depth guide that merges machine learning techniques with OpenCV, the most popular computer vision library, using Python. The book introduces fundamental concepts in machine learning and computer vision, progressing to practical implementation with OpenCV. Concepts related to image preprocessing, contour and thresholding techniques, motion detection and tracking are explained in a step-by-step manner using code and output snippets. Hands-on projects with real-world datasets will offer you an invaluable experience in solving OpenCV challenges with machine learning. It's an ultimate guide to explore areas like deep learning, transfer learning, and model optimization, empowering readers to tackle complex tasks. Every chapter offers practical tips and tricks to build effective ML models. TABLE OF CONTENTS 1. Getting Started with HTML, CSS, and Tailwind CSS 2. Design Principles for Tailwind CSS 3. Utility-First Classes and Customization Options 4. Element-Specific Styling with Utility- First Classes 5. Developing a Website with Tailwind CSS 6. Advanced Website Development with Tailwind CSS 7. Best Practices for Tailwind CSS Index

DESCRIPTIONThis book is an in-depth guide that merges machine learning techniques with OpenCV, the most popular computer vision library, using Python. The book introduces fundamental concepts in machine learning and computer vision, progressing to practical implementation with OpenCV. Concepts related to image preprocessing, contour and thresholding techniques, motion detection and tracking are explained in a step-by-step manner using code and output snippets. Hands-on projects with real-world datasets will offer you an invaluable experience in solving OpenCV challenges with machine learning. It's an ultimate guide to explore areas like deep learning, transfer learning, and model optimization, empowering readers to tackle complex tasks. Every chapter offers practical tips and tricks to build effective ML models. ¿TABLE OF CONTENTS Chapter 1: Getting Started With OpenCV Chapter 2: Basic Image & Video Analytics in OpenCVChapter 3: Image Processing 1 using OpenCVChapter 4: Image Processing 2 using OpenCVChapter 5: Thresholding and Contour Techniques Using OpenCV Chapter 6: Detect Corners and Road Lane using OpenCVChapter 7: Object And Motion Detection Using OpencvChapter 8: Image Segmentation and Detecting Faces Using OpenCVChapter 9: Introduction to Deep Learning with OpenCVChapter 10: Advance Deep Learning Projects with OpenCVChapter 11: Deployment of OpenCV projectsBy the end, you would have mastered and applied ML concepts confidently to real-world computer vision problems and will be able to develop robust and accurate machine-learning models for diverse applications. Whether you are new to machine learning or seeking to enhance your computer vision skills, This book is an invaluable resource for mastering the integration of machine learning and computer vision using OpenCV and Python.

DESCRIPTIONThis book provides a comprehensive guide to TypeScript, a programming language that extends JavaScript with powerful features like static typing, classes, and interfaces. The book is divided into thirteen chapters that cover everything from setting up a development environment to building an Angular app with TypeScript. We start with an introduction to TypeScript and its benefits and go on to explain how TypeScript can help developers write more maintainable, scalable code and catch errors before they make it to production. The book then dives into more technical topics like basic type annotations, using the TypeScript compiler, advanced features like enums and interfaces, and manipulating types. TABLE OF CONTENTS Chapter 1: Introduction to TypeScript and its BenefitsChapter 2: Setting Up a Development EnvironmentChapter 3: Basic Type AnnotationsChapter 4: Using the TypeScript CompilerChapter 5: Enums, Interfaces, and NamespacesChapter 6: Objects, Arrays, and Tuples in TypeScriptChapter 7: Functions in TypeScriptChapter 8: Classes in TypeScriptChapter 9: Control Flow AnalysisChapter 10: Manipulating TypesChapter 11: TypeScript ModulesChapter 12: Creating Declaration FilesChapter 13: TypeScript Project: Creating an Angular App

This book will teach you everything about the powerful techniques and applications of parallel computing, from the basics of parallel programming to the cutting-edge innovations shaping the future of computing. The book starts with an introduction to parallel programming and the different types of parallelism, including parallel programming with threads and processes. The book then delves into asynchronous programming, distributed Python, and GPU programming with Python, providing you with the tools you need to optimize your programs for distributed and high-performance computing. The book also covers a wide range of applications for parallel computing, including data science, artificial intelligence, and other complex scientific simulations. You will learn about the challenges and opportunities presented by parallel computing for these applications and how to overcome them. By the end of the book, you will have insights into the future of parallel computing, the latest research and developments in the field, and explore the exciting possibilities that lie ahead.TABLE OF CONTENTS 1. Introduction to Parallel Programming 2. Building Multithreaded Programs 3. Working with Multiprocessing and mpi4py Library4. Asynchronous Programming with AsyncIO5. Realizing Parallelism with Distributed Systems 6. Maximizing Performance with GPU Programming using CUDA7. Embracing the Parallel Computing Revolution8. Scaling Your Data Science Applications with Dask9. Exploring the Potential of AI with Parallel Computing10. Hands-on Applications of Parallel Computing

DESCRIPTIONCloud platforms face unique security issues and opportunities because of their evolving designs and API-driven automation. We will learn cloud-specific strategies for securing platforms such as AWS, Microsoft Azure, Google Cloud Platform, Oracle Cloud Infrastructure, and others. The book will help you implement data asset management, identity and access management, network security, vulnerability management, incident response, and compliance in your cloud environment.WHAT WILL YOU LEARN ¿ Understand the critical role of Identity and Access Management (IAM) in cloud environments.¿ Address different types of security vulnerabilities in the cloud.¿ Develop and apply effective incident response strategies for detecting, responding to, and recovering from security incidents.¿ Establish a robust and secure security system by selecting appropriate security solutions for your cloud ecosystem.TABLE OF CONTENTS SECTION I: Overview and Need to Transform to Cloud Landscape1. Evolution of Cloud Computing and its Impact on Security 2. Understanding the Core Principles of Cloud Security and its Importance3. Cloud Landscape Assessment and Choosing the Solution for Your EnterpriseSECTION II: Building Blocks of Cloud Security Framework and Adoption Path4. Cloud Security Architecture and Implementation Framework5. Native Cloud Security Controls and Building Blocks6. Examine Regulatory Compliance and Adoption path for Cloud 7. Creating and Enforcing Effective Security PoliciesSECTION III: Maturity Path8. Leveraging Cloud-based Security Solutions for Security-as-a-Service9. Cloud Security Recommendations and Best Practices