Page 81 - AI & Machine Learning for Beginners: A Guided Workbook
P. 81
Chapter 7
Extras - Supplementary Content
This chapter offers supplementary content to enhance your AI
learning journey! Dive into a comprehensive glossary of AI and
machine learning terms, explore thought-provoking quotes from
influential tech leaders, and use the blank space for notes,
reflections, and mind maps to capture your ideas.
Whether you're expanding your knowledge or brainstorming new
insights, these extras provide a valuable reference to support your
AI exploration!
Glossary of AI/ML Terms
Algorithm – A step-by-step procedure for solving a problem or
accomplishing a task in AI and ML.
Artificial General Intelligence (AGI) – A hypothetical form of AI
with human-like cognitive abilities, capable of reasoning and
learning across multiple domains.
Bias – Systematic errors in AI systems that can result in unfair
or imbalanced decision-making, often caused by skewed training
data or flawed algorithm design.
Big Data – Massive, complex datasets that AI models use for
training and analysis.
Classification – An ML task that involves assigning predefined
categories to input data.
Clustering – Grouping similar data points without predefined
categories, allowing AI to discover patterns independently.
79
