(Weeks 7–8 | Lecture 6 Hrs / Lab 18 Hrs / Ext 0 Hrs | 24 Total Contact Hrs | 1.0 Semester
Credit)
Students will:
- Build deep neural networks from scratch using TensorFlow/Keras.
- Train models using backpropagation and advanced optimization techniques.
- Apply regularization methods such as dropout and batch normalization.
Prerequisite: MLDL 103 – Unsupervised Learning & Clustering
Tools: TensorFlow, Keras
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