Explain the rationale behind the structural progression of ML Yearning.
Question: In Machine Learning Yearning, the content is structured to progress from general strategies (applicable to traditional algorithms) to modern deep learning strategies. Analyze why establishing a foundation in general strategies is beneficial before tackling complex deep learning systems.
Sample answer: Starting with general strategies establishes foundational principles that govern ML system building, regardless of the algorithm. Since the process of building these systems is complex, general strategies provide robust structural frameworks. Once these are understood, they can be adapted and scaled for the modern strategies required by deep learning, ensuring developers have a solid baseline.
Key points:
- Building ML systems is a complex process.
- General strategies apply to both traditional algorithms and neural networks.
- Foundational knowledge prepares developers for modern deep learning strategies.
Rubric: Answers should discuss the complexity of ML systems and the foundational value of general strategies before moving to specialized deep learning techniques.
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Machine Learning
Deep Learning
Supervised Learning
Dive into Deep Learning @ D2L
Data Science
Machine Learning Strategy
Machine Learning Yearning @ DeepLearning.AI
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