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Unit I
Deep Feedforward Networks: Artificial Neural Networks, Artificial Neuron, Example:
Learning XOR, Gradient-Based Learning, Hidden Units, Architecture Design, Back-Propagation and Other Differentiation Algorithms, Regularization for Deep Learning- Parameter Norm Penalties, Dataset Augmentation, Noise Robustness, Early Stopping, Dropout, Adversarial Training, Optimization for Training Deep Models- How Learning Differs from Pure Optimization? Challenges in Neural Network Optimization, Basic Algorithms- Stochastic Gradient Descent, momentum. Parameter Initialization Strategies, Algorithms with Adaptive Learning Rates, Optimization Strategies and Meta-Algorithms.
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As per the latest IPU syllabus — cross-check electives with your college.
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Deep Learning (AIML308) is a semester 6 subject in the IPU B.Tech AI & ML (Artificial Intelligence and Machine Learning) (AI-ML) curriculum.
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