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Mindforge ML | Unit 4 – Podcast 01_Title: The Architecture of Supervised Learning
Supervised Learning forms the core of practical Machine Learning systems.
This master episode introduces the complete architecture of supervised learning — from labeled data to model evaluation — building a conceptual map for the entire unit.
Key topics:
Labeled Data: Understanding input–output mapping.
Regression vs Classification: Continuous and discrete prediction problems.
Algorithm Overview: Decision Tree, KNN, SVM, Linear and Logistic Regression.
Evaluation Thinking: Why model performance matters.
This episode sets the foundation for deeper exploration of supervised learning algorithms.
Series: Mindforge ML
Produced by: Chatake Innoworks Pvt. Ltd.
Initiative: MindforgeAI
View all episodes
By CI CodesmithSupervised Learning forms the core of practical Machine Learning systems.
This master episode introduces the complete architecture of supervised learning — from labeled data to model evaluation — building a conceptual map for the entire unit.
Key topics:
Labeled Data: Understanding input–output mapping.
Regression vs Classification: Continuous and discrete prediction problems.
Algorithm Overview: Decision Tree, KNN, SVM, Linear and Logistic Regression.
Evaluation Thinking: Why model performance matters.
This episode sets the foundation for deeper exploration of supervised learning algorithms.
Series: Mindforge ML
Produced by: Chatake Innoworks Pvt. Ltd.
Initiative: MindforgeAI