Official Bihar Engineering University examination question papers, marks distribution, and questions transcript. Available exam sessions: 2025.
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Official BEU curriculum units & topics for this examination subject.
Unit 1.0: Introduction
Definition of AI, Machine Learning, Deep Learning • Human Brain vs Artificial Neuron, Biological neuron and artificial neuron analogy • Neuron Models: McCulloch-Pitts neuron, Activation functions (Sigmoid, Tanh, ReLU, Leaky ReLU, Softmax) • Perceptron, Multilayer Perceptrons, Back-Propagation Algorithm, XOR Problem • Difficulty of training deep neural networks, Discussion on deep learning frameworks
Unit 2.0: Optimization & Hyperparameter Tuning
Gradient Descent, stochastic gradient, momentum, RMSProp, ADAM • Regularization for Deep Learning: Parameter Norm Penalties - L2 Parameter Regularization, Dataset Augmentation, Semi-Supervised Learning • Optimization for Training Deep Models
Unit 3.0: Convolutional Neural Networks (CNN)
Convolution operation, Filters, Padding, Stride, Pooling, Normalization • Modern CNN architectures: LeNet, AlexNet, VGG, GoogLeNet, ResNet, Inception, EfficientNet • Transfer Learning & Fine-tuning, Image Augmentation
Unit 4.0: Sequence Modeling
RNN, Vanishing Gradient in RNN, LSTM & GRU networks, Bidirectional RNNs • Applications: Text generation, Sentiment analysis, Time-series forecasting
Unit 5.0: Attention and Transformers
Attention mechanism (Self-attention, Multi-head) • Positional Autoencoders, Encoder-Decoder architecture, Sparse Autoencoders, Denoising Autoencoders, Variational Autoencoders (VAE) • Transformer architecture, BERT, GPT