Difference Between Algorithm and Model in Machine Learning (2026 Guide)

What is the difference between an Algorithm and a Model? In this video, we break down the most important Machine Learning terminologies every beginner must know. Using a simple "Cupcake Recipe" analogy, I explain how algorithms find patterns to create trained models.
We also dive into the Diabetes dataset to explain Predictor variables (Features) vs. Response variables (Output), and why we split data into Training and Testing sets (the 80/20 rule). This is a two-part foundational lesson for our Free Placement Course.
📌 TIMESTAMPS:
00:00 - Intro: Why Terminologies Matter
00:20 - What is an Algorithm? (The T-Shirt Box Analogy)
01:25 - What is a Model? (The Trained Output)
02:47 - Predictor Variables vs. Response Variables (Features vs. Label)
03:45 - Training Data vs. Testing Data (The 80/20 Split)
05:10 - The Cupcake Analogy: Algorithms as Recipes
09:42 - Applying Terms to the Diabetes Dataset
11:45 - Part 2: Deep Dive into ML Models
12:55 - Comparing Algorithms: Logistic Regression vs. Decision Trees vs. SVM
14:55 - How to Calculate Model Accuracy
16:45 - Summary: Algorithm vs. Model Final Breakdown
🔗 RESOURCES:
Join the Free Placement Course: [https://youtube.com/@freeplacementcourse?si=r35F3mTq5ThYSMV9]

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Видео Difference Between Algorithm and Model in Machine Learning (2026 Guide) канала freeplacementcourse