Deep Learning Lab

This repository contains implementations of various deep learning experiments using both PyTorch and TensorFlow.

Experiments

1. Machine Learning Fundamentals

• 1_a_decision_tree.py - Decision Tree classifier on Iris dataset
• 1_b_svm.py - SVM with decision boundary visualization
• 1_c_gradient_descent.py - Gradient descent implementation + visualization
• 2_linear_regression.py - Linear regression on synthetic data + visualization

2. Neural Networks

• 3_image.py / 3_tensor.py - Image enhancement operations such as histogram equalization, morphological operations
• 4_Neural_network.py / 4_tensor.py - Feedforward Neural Network on CIFAR-10 dataset
• 5_initialization_regularization.py / 5_tensor.py - Analyzing the impact of Weight initialization and regularization on network's performance in terms of accuracy and prevention of overfitting

3. Convolutional Neural Networks

• 6_Digit.py / 6_tensor.py - Convolutional Neural Network (CNN) for digit classification on the MNIST dataset
• 7_Digit_VGGNet.py / 7_tensor__.py - VGGNet-19 implementation for digit classification for MNIST dataset

4. Recurrent Neural Networks

• 8_RNN_imdb_kaggle.py / 8_tensor.py - Recurrent Neural Network (RNN) for review classification on the IMDB dataset
• 9_RNN_LSTM.py / 9_Tensorflow.py - RNN vs LSTM vs GRU comparison for sentiment analysis on the IMDB dataset

5. Advanced Applications

• 10_NIFTY.py / 10_tensor.py - Stock price prediction: Time series forecasting for the NIFTY-50 dataset
• 11_Machine_Translation.py / 11_tensorflow.py - Shallow autoencoder and decoder network for English to Hindi translation using LSTM

Additional Files

• 3_sample_image.png - Sample image for experiment 3
• z_labexam.py - Lab exam question: Spam Detection using GRU
• viva.docx - Viva questions and answers for lab exam

🤝 Contributing

This is an academic project for S7 Deep Learning lab. Programs are designed for educational purposes and demonstrate core Neural Network concepts.

📄 License

Educational use only - S7 DL Laboratory Programs

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Developed for Deep Learning Laboratory - 7th Semester AI & ML