Machine Learning Foundations | Part 4 (Urdu/Hindi)

In this video, we explain learning, objective functions, and optimization in Machine Learning using clear and simple concepts.

You’ll learn

• Objective function – definition and purpose
• Types of objective (loss) functions
• What learning means in Machine Learning
• Optimization of objective functions
• Error rate and its role in learning
• Model parameters and updates
• Dataset splitting (train vs test)
• Training process explained
• Testing and evaluation basics
• Overfitting and why it happens
• Introduction to optimization algorithms
• Purpose of optimization in ML
• Gradient Descent – basic intuition
This video is Part 4 of the Machine Learning Foundations series and builds the foundation for advanced ML and Deep Learning algorithms.
👉SEE Also (Related Videos):
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https://youtu.be/dLJFHL1Q3rE
👉Machine learning Foundations | Part 2 (Urdu/Hindi)
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👉Deep Learning Mathematical Foundations | Part 4 (Gradients and Chain Rule) Urdu/Hindi
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👉Deep Learning Mathematical Foundations | Part 3 (Derivatives and Partial Derivatives) Urdu/Hindi
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👉Deep Learning Mathematical Foundation | Part 2 (Urdu/Hindi)
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👉Deep Learning Mathematical Foundation | Part 1 (Urdu/Hindi)
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👉Deep Learning Course Overview | Complete Syllabus & Roadmap
https://youtu.be/o9RBnCNKX64
👉Deep Learning From Scratch | Instructor Introduction & Complete Course Overview
https://youtu.be/bG1fG_hNNdY
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Видео Machine Learning Foundations | Part 4 (Urdu/Hindi) канала Quick Research Reviews (QRR)