dl mid term syllabus:

dl mid term syllabus:

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📢 Mid Exam Important Instructions 

🔹 1. Neural Network (Very Important)

• You must prepare Neural Networks (NN) properly.

• Focus on:

  • Feed Forward Neural Network

  • Backpropagation Neural Network

• Important things to cover:

  • Complete conceptual understanding

  • Graph/diagram representation

  • Working/flow (step by step)

• Numerical questions from NN are expected.

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🔹 2. Mathematical Part

• Be prepared for mathematical derivation (especially from backpropagation).

• Practice solving numericals clearly step by step.

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🔹 3. Hyperparameters

• Around 10–12 hyperparameters were discussed in class.

• You must:

  • Remember their names

  • Understand their roles

• Examples:

  • Learning rate

  • Batch size

  • Epochs

  • etc.

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🔹 4. CNN (Convolutional Neural Network)

• Important topics:

  • CNN architecture

  • Training process

  • Models of CNN

• Also prepare:

  • How to select hyperparameters

  • How to use optimization algorithms

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🔹 5. Transfer Learning

• Must prepare:

  • Concept & understanding

  • Approaches

  • Implementation

• Important concepts:

  • Pre-trained models

  • Freezing layers

  • Feature extraction

• Know different models that can be used.

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🔹 6. NLP (Natural Language Processing)

• Focus on:

  • Applications of NLP

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🔥 Final Advice

• Prepare all topics, don’t skip anything

• Focus more on:

  • NN (Backprop + Feedforward)

  • CNN

  • Transfer Learning

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