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
1
Introduction
2
A Brief History
3
AI Building Blocks
4
The 3 Stages of AI Development
5
Machine Learning
6
Deep Learning
7
Natural Language Processing
8
Generative AI
9
Recommender Systems
10
Computer Vision
11
Privacy & Ethical Considerations
12
The Future of Work
13
Further Resources

Recommender Systems

 

In an era of information overload, recommender systems have become an indispensable tool for steering people through the vast ocean of content and navigating the long tail of available products. Fueled by data and algorithms, recommender systems can analyze our behaviors and preferences and then deliver personalized recommendations tailored to our unique tastes and interests. By recommending movies, music, books, products, and other items, they save us valuable time while opening doors to new discoveries.

In this chapter, we’ll delve into the exciting world of recommender systems, explore various approaches, and uncover strategies to maximize their performance. Before we get started, it’s important to acknowledge that recommender systems are not built on a single technique or one family of algorithms. Instead, they represent a mismatch of techniques and algorithms united under one common goal: to make relevant recommendations. Whether it’...