Artificial Intelligence: Machine Learning, Deep Learning, and Automation Processes

A practical introduction to AI, machine learning, and automation

Artificial Intelligence: Machine Learning, Deep Learning, and Automation Processes by John Adamssen is a beginner-friendly overview of how AI is used, why it matters, and where its limits still show. Rather than staying at the level of buzzwords, the book moves through the basic logic of AI, the role of data, and the core ideas behind machine learning and deep learning in a way that is meant to be approachable.

The opening chapters trace the history of AI and explain how modern systems work, including neural networks, natural language processing, computer vision, and the technologies that support them. Later sections turn to data analytics and the value of data-driven decision-making, before closing with examples of AI already visible in daily life.

What the book emphasizes

• How AI systems learn from data and improve over time
• The difference between machine learning, deep learning, and related AI subfields
• Why data quality and scale affect results
• How businesses use analytics to identify patterns and opportunities
• Real-world AI applications such as assistants, search, and automation

Why it stands out

The emphasis here is practical understanding. The book is written for readers who want a broad, readable guide to AI concepts without getting lost in heavy theory. It is especially useful for newcomers, students, and business readers who want a clearer picture of how modern AI systems are put together and where they are already being applied.

If you want a concise, non-technical introduction to the language of artificial intelligence, this title offers a straightforward place to start.