Book Image

AI for Absolute Beginners: A Clear Guide to Tomorrow

By : Oliver Theobald
4 (1)
Book Image

AI for Absolute Beginners: A Clear Guide to Tomorrow

4 (1)
By: Oliver Theobald

Overview of this book

The course begins with an engaging introduction to the world of Artificial Intelligence, making it approachable for absolute beginners. We unravel the mysteries of AI's evolution, from its historical roots to the cutting-edge technologies shaping our future. By explaining complex concepts in simple terms, this course aims to illuminate the path for those curious about how AI impacts our world. The course focuses on the core components of AI, including machine learning, deep learning, and natural language processing, before advancing to more specialized topics like generative AI and computer vision. Each module is designed to build a comprehensive understanding, emphasizing why these technologies are crucial for solving real-world problems and how they're transforming industries. The course wraps up by exploring the ethical considerations and privacy concerns associated with AI, along with a visionary look at the future of work in an AI-driven world. It offers a treasure trove of further resources, ensuring learners have everything they need to continue their exploration of AI.
Table of Contents (13 chapters)
Free Chapter
A Brief History
AI Building Blocks
The 3 Stages of AI Development
Machine Learning
Deep Learning
Natural Language Processing
Generative AI
Recommender Systems
Computer Vision
Privacy & Ethical Considerations
The Future of Work
Further Resources

Natural Language Processing


Beyond numerical data, a vast amount of human knowledge and experience is captured in text and audio. The ubiquity of words in daily life and the need for effective human-computer interactions make the ability to process human language a crucial part of artificial intelligence.

As a multidisciplinary field straddling linguistics, computer science, and AI, natural language processing empowers computers with the capability to understand and reproduce human language. Inspired by linguistics—the study of language and semantics—NLP was originally designed for parsing text in databases using coding rule systems, but over time, it merged with common algorithms from machine learning to evolve into a novel and specialized field of computational linguistics. Now, as a field of its own, NLP involves analyzing human language with reduced emphasis on quantitative problem-solving, which is typically the focus of other subfields related to AI.