AI Strategies for Web Development 1st Edition by Anderson Soares Furtado Oliveira ISBN 1835886302 9781835886304 by Anderson Soares Furtado Oliveira instant download after payment.

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ISBN 10: 1835886302 
ISBN 13: 9781835886304
Author: Anderson Soares Furtado Oliveira

From fundamental to advanced strategies, unlock useful insights for creating innovative, user-centric websites while navigating the evolving landscape of AI ethics and security

Key Features
Explore AI's role in web development, from shaping projects to architecting solutions
Master advanced AI strategies to build cutting-edge applications
Anticipate future trends by exploring next-gen development environments, emerging interfaces, and security considerations in AI web development
Purchase of the print or Kindle book includes a free PDF eBook
Book Description
If you’re a web developer looking to leverage the power of AI in your projects, then this book is for you. Written by an AI and ML expert with more than 15 years of experience, AI Strategies for Web Development takes you on a transformative journey through the dynamic intersection of AI and web development, offering a hands-on learning experience. The first part of the book focuses on uncovering the profound impact of AI on web projects, exploring fundamental concepts, and navigating popular frameworks and tools. As you progress, you’ll learn how to build smart AI applications with design intelligence, personalized user journeys, and coding assistants. Later, you’ll explore how to future-proof your web development projects using advanced AI strategies and understand AI’s impact on jobs. Toward the end, you’ll immerse yourself in AI-augmented development, crafting intelligent web applications and navigating the ethical landscape. Packed with insights into next-gen development environments, AI-augmented practices, emerging realities, interfaces, and security governance, this web development book acts as your roadmap to staying ahead in the AI and web development domain.
What you will learn
Build AI-powered web projects with optimized models
Personalize UX dynamically with AI, NLP, chatbots, and recommendations
Explore AI coding assistants and other tools for advanced web development
Craft data-driven, personalized experiences using pattern recognition
Architect effective AI solutions while exploring the future of web development
Build secure and ethical AI applications following TRiSM best practices
Explore cutting-edge AI and web development trends
Who this book is for
This book is for web developers with experience in programming languages and an interest in keeping up with the latest trends in AI-powered web development. Full-stack, front-end, and back-end developers, UI/UX designers, software engineers, and web development enthusiasts will also find valuable information and practical guidelines for developing smarter websites with AI. To get the most out of this book, it is recommended that you have basic knowledge of programming languages such as HTML, CSS, and JavaScript, as well as a familiarity with machine learning concepts.

AI Strategies for Web Development 1st Table of contents:

Part 1: Embarking on the AI Revolution in Web Development
Chapter 1: AI’s Role in Shaping Web Development
Demystifying AI in web development
Introduction to the principles of AI
AI problem-solving landscape
AI’s transformative role in web development
Case study – Coca-Cola’s “Create Real Magic” platform
AI-powered transformations in web design
Why is AI’s presence in web design not just a trend but a necessity?
Key concepts in AI-powered web design
AI’s benefits for web design
The synergy of AI and user experience
The transformative impact of AI on UX
Case study – Dell conquers marketing challenges with Persado – a data-driven, customer-centric success story
User-centric AI-driven development
Navigating through AI-driven development tools
AI-powered tools and technologies for web development
Key considerations in navigating AI-driven development tools
Ethical considerations in AI-enhanced web development
Summary
Chapter 2: Mastering the Essentials – AI Fundamentals
Technical requirements
AI fundamentals – a deep dive
The historical journey of AI
Understanding the science and techniques behind AI programming
Advantages and disadvantages of AI
Exploring the three main categories of AI
Understanding the four types of AI
Exploring the inner workings of AI for web developers
Main AI applications
Machine learning essentials
What is machine learning?
Types of machine learning algorithms
NLP for web interaction
Key components of NLP
The power of large language models in web development
Applications of NLP in web interaction
Classifications of NLP
Introduction to neural networks
Fundamental concepts of neural networks
Types of neural networks
Training neural networks
Application of neural networks in web development
Empowering web development with computer vision
Key concepts in CV
Applications of CV in web development
Technologies and tools for CV
Summary
Chapter 3: Challenges and Opportunities – Integrating AI into Web Projects
Technical requirements
Navigating the AI process in web development
Defining the processes
The importance of each process
Integrating the processes
AI pipeline – streamlining the journey of AI
Integrated AI loops – streamlining AI development for web applications
Selecting and evaluating models for web-based AI
Procedure
Observations
Ethical considerations in AI integration
Challenges in ethical AI integration
Mitigating risks in AI implementation
Ethical AI frameworks
Diverse and inclusive AI development teams
Ensuring optimal performance of AI models through continuous monitoring and maintenance
Explainability and interpretability – enhancing model interpretability and communicating AI decisions effectively
Robust data governance – implementing strong data governance policies and data quality assurance
Human oversight and intervention – ensuring accuracy and fairness in AI for web development
Unveiling the importance of regular auditing and documentation for bias and fairness in AI systems
Making models understandable with interpretable AI
Example of integrating AI into web projects – personalized movie recommendations with AI
Introducing the sklearn library
Getting started – loading the MovieLens dataset and training a machine learning model
Summary
Chapter 4: Navigating the Landscape: Popular AI and ML Frameworks and Tools
Technical requirements
Data Set
Integrated Development Environment (IDE)
Project Structure
Version Control
Environment Management
System Requirements
A deep dive into AI Frameworks
Mastering AI Frameworks: A comprehensive guide
Indispensable tools for Artificial Intelligence in web development
AI libraries
Natural Language Processing (NLP) Tools
Computer vision tools
Tools and frameworks for deploying AI models
Monitoring and logging for AI systems: Ensuring performance, health, and optimization
Delving into frameworks for web development
Popular web development frameworks
Exploring Synergy: Uniting Web Interfaces with Powerful AI
Optimization of AI development environments
Setting up development environments
AI Development with Docker
Exploring Git’s Vital Role in AI Development
Cloud Platforms: Scaling, Speed, and Efficiency in AI Development
Choosing the right tools for your project
Project requirements
Analyzing the tools
Decision-making
Example: Building a Sentiment Analysis Web Application
Project overview
Database description
Applying tool selection guide
Getting started on the model
Summary
Chapter 5: Blueprints of the Future – Architecting Effective AI Solutions
Fundamentals of AI architecture
Essential components
The crucial role of interfaces in AI solutions
Scalable and efficient AI solutions architecture for web projects
The importance of the data life cycle in building efficient AI solutions
Typical architectures of AI solutions
Designing AI solutions – a step-by-step guide
Implementation of solutions
Ensuring maintainability and adaptability
Architecting the future – unleashing the power of AI solutions through the AI Architecture Framework
Context
Data life cycle
Architecture design
Real-world AI architecture use cases – ChatGPT by OpenAI
Context
Data life cycle
Architecture design
Introduction to Architect Your AI (AYAI) Framework
Summary
Part 2: Crafting the Future: Creating Cutting-Edge AI Applications
Chapter 6: Design Intelligence – Creating User-Centric Experiences with AI
Technical Requirements
Navigating the World of Design Intelligence in Web Development
Components of DI
Phases of the DI process
Benefits of DI
Challenges of DI
Applying AI for personalized user experiences
Harnessing AI algorithms for tailored user experiences
Example of AI Movie Recommendation Chatbot
Optimizing user interfaces with AI
Practical applications of User Support, Accessibility, and Personalized Experiences
Measuring the impact of AI-Enhanced User Interfaces
Metrics for impact assessment
AI-specific metrics
Gathering user feedback
Iterative design process
Summary
Chapter 7: Recognizing Patterns – Personalizing User Journeys with AI
Technical requirements
Cracking the code of pattern recognition principles
Understanding the principles of pattern recognition
Key components of pattern recognition
Personalization techniques – a practical approach
Dynamic content delivery
Predictive personalization
Behavioral targeting
Predictive algorithms for personalization
Key predictive algorithm techniques
Machine learning models
Broad applications in personalization techniques
Implementing recommendation systems
Example – a movie recommendation system with machine learning
Creating a unified AI entity
Exploring the main components of a unified AI entity
Enhancing AI through interconnectivity
Technical challenges and solutions
Key aspects of interconnectivity
Implementation strategies
Summary
Chapter 8: Coding Assistants – Your Secret Weapon in Modern Development
Mastering coding assistants
Code generators
Understanding GitHub Copilot
Integrating coding assistants into your workflows
Setting up GitHub Copilot in VS Code – a step-by-step guide
Prerequisites for using GitHub Copilot
Managing coding assistants in a team environment with GitHub Copilot
Maximizing productivity with smart code suggestions
Rapid code writing
Harnessing the power of GitHub Copilot Chat in VS Code
Using multilingual capabilities
Code optimization tips
Detecting and fixing errors with intelligent debugging
Real-time error detection
Debugging using chat and VS Code
Adjusting code with the Fix This feature
Generating unit tests with GitHub Copilot
Streamlining collaboration through code review assistance
Enhancing the code review process
Ensuring code quality
Team collaboration features
Summary
Chapter 9: Smarter User Interactions – Elevating User Engagement with Advanced AI
Technical requirements
Unraveling advanced AI for user interactions
Unraveling the mysteries of conversational AI – a deep dive into its types, techniques, and applications
Creating conversational experiences with chatbots
Mastering the art of conversational UI design for chatbots
Tips for creating engaging dialogues for chatbots
Building chatbot architectures – understanding the different types of chatbots
Integrating chatbots with existing systems – connecting chatbots to databases, APIs, and services
A step-by-step guide to building a chatbot using the Natural Language Toolkit (NLTK)
Harnessing the power of voice recognition
A practical guide for web developers – implementing voice interactions
Audio transcription with the SpeechRecognition library – a step-by-step guide for web developers
Analyzing language patterns for personalized interactions
Generative language models and the future of content creation
A step-by-step guide to integrating a generative language model into your development workflow
Exploring text generation with GPT-2 Simple
The example of an AI movie recommendation chatbot
Project overview
Key features
Data description
Step-by-step Python code
Detailed steps to configure the bot
Testing the chatbot
Summary
Chapter 10: Smart Testing Strategies – Fortifying Web Applications with AI Insights
Introduction to Smart Testing with AI
Key concepts and implementation
AI-Enhanced Performance Testing
Python Libraries for Performance Testing
Enhancing Performance Testing with Machine Learning
Intelligent Security Testing Protocols
Python Libraries for Enhanced Security Testing
Python Code Examples for Intelligent Security Testing
AI-Driven Bias Detection and Mitigation
Understanding bias, its detection and integration
AI Bias Detection Libraries
Reliability and Validity Assurance through AI
Testing and best practices
Python Libraries for Reliability and Validity Testing
Summary
Part 3: Future-Proofing Web Development – Advanced AI Strategies
Chapter 11: Augmented Workforce – AI’s Impact on Web Development Jobs
Conceptualizing an augmented workforce
Navigating the AI revolution in web development jobs
Strategic implementation of an augmented workforce in web development
Accelerating digital skills and reducing time to competency
Getting started – practical steps for implementation
Summary
Chapter 12: Machine Users Unveiled – Navigating the Intersection of Human and Machine
Decoding machine customers – understanding the future of consumerism
Use case – smart refrigerators connected to local supermarkets
Market opportunities and scenarios
Considerations
Industry-specific opportunities
Thriving in a competitive market
Understanding regulations and trends
Case study – gas station service for autonomous cars
Requirements
Operational management
Essential components
Data flow
Architecture design
Impact on purchases and commerce
Preparing for the future with MCs
Summary
Chapter 13: AI-Augmented Development – Shaping Tomorrow’s Digital Landscape
The impact of AI-augmented development on software engineering
Understanding the AI-augmented development components
Enhancing the software development life cycle with Gemini Code Assist
Gemini Code Assist – an AI-augmented development tool
Practical strategies for leveraging AI in software development
How to integrate AI into software development teams
Summary
Further reading
Chapter 14: From Idea to Reality – Crafting Intelligent Web Applications
Intelligent applications – revolutionizing the future of technology
Building an intelligent chatbot for e-commerce – laying the groundwork
Data and design – creating an intelligent chatbot for e-commerce
Building blocks of AI integration – integrating intelligent features for a smart e-commerce chatbot
Deployment and user engagement – utilizing AI for business analytics and web application
Evolution through learning – unlock the potential of AI for business analytics
Summary
Chapter 15: Guardians of the Digital Realm – Navigating Trust, Risk, and Ethics in AI
Fundamental principles of AI ethics
Key ethical principles in AI development
Examples of precautionary measures in AI projects
Applying ethical concepts in AI development
Structuring and implementing governance frameworks for AI models
Understanding the importance of governance
Considerations for implementing governance frameworks
Understanding and applying the AI TRiSM framework
The core of AI TRiSM
Implementation and responsibilities within AI TRiSM
Embarking on the AI TRiSM journey
Creating business value through TRiSM
Implementing TRiSM for creating business value
The crucial role of AI professionals in web development
ISO standards and guidelines for TRiSM implementation
Summary
Part 4: The Road Ahead – Anticipating Trends in AI and Web Development
Chapter 16: Next-Gen Development Environments and Advancements in AI Technologies
The GitOps revolution and implementing GitOps principles for streamlined workflows
Implementing GitOps for streamlined workflows
Best practices in GitOps
Embracing the cloud for enhanced development and leveraging cloud tools and resources
Collaboration best practices in next-gen development
Exploring neuro-symbolic AI, FML, and WebAssembly
Neuro-symbolic AI
FML – a new paradigm
WebAssembly
Summary
Chapter 17: Emerging Realities and Interfaces
VR/AR and web development
AR hardware requirements and compatibility
Challenges and limitations
Potential solutions
VR/AR in web development
Crafting immersive digital experiences
Real-world applications of VR/AR in web development
Exploring CUIs and web development
Utilizing NLP techniques
Designing intuitive conversation flows
Incorporating personality and tone into the interface
Implementing context-aware responses
Testing and iterating the conversational interface for an optimal user experience
Ubiquitous computing and web development
Key technologies
Applications in web development
Summary
Chapter 18: AI Regulation and Governance – Compliance with the EU’s AI Act and ISO/IEC 42001 Standards
Overview of AI regulations
The EU’s AI Act
Understanding ISO/IEC 42001
Overview of the G³AI framework
Purpose of the G³AI framework
Structure of the G³AI framework
The G³AI metamodel
AI strategy
AI governance
Structuring internal controls
Performance evaluation and continuous improvement
AI management
Planning and implementing the AI management system
Continuous integration/continuous deployment (CI/CD) in AI management
Summary
Further reading
Index
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