Page 31 - AI & Machine Learning for Beginners: A Guided Workbook
P. 31
Ingredients = Data → Raw materials that feed the algorithm
(e.g., images, numbers, words).
Instructions = The Algorithm → A structured method that
analyzes the data, identifies patterns, and processes information.
The Dish = The Model → The learned outcome that can make
predictions, classify data, or automate tasks.
Simple Example: Baking a Cake
Think of a cake recipe:
• You start with ingredients like flour, sugar, and eggs (data).
• You follow instructions on mixing, baking, and decorating
(algorithm).
• The finished cake is your final product, which embodies
the learned pattern—just like a trained ML model that
"predicts" the characteristics of future cakes.
• The finished cake is your final product, which embodies the
learned pattern, just like a trained ML model that "predicts"
the characteristics of future cakes.
Real-Life Analogy: An algorithm is like a recipe. Just as
a recipe tells you the ingredients and steps to make a dish,
an algorithm suggests to a computer what operations to
perform and in what order.
Your Turn: Think of something you do regularly that
follows a specific sequence. Write it as a step-by-step
algorithm:
1.
2.
3.
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