/CS405-Deep-Learning

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CS405 Deep Learning Course Labs

Welcome to the CS405 Deep Learning course labs repository! This repository contains the lab assignments completed during the CS405 Deep Learning course at National University of Sciences & Technology (NUST), Pakistan. Each lab focuses on various aspects of deep learning and neural networks.

Lab Experiments

  1. Lab-1: Introduction to Python: A foundational lab introducing you to Python, a widely used programming language in the field of deep learning.

  2. Lab-2: Basics of Neural Networks using numpy: Learn the fundamentals of neural networks using numpy, a fundamental library for numerical computing in Python.

  3. Lab-3: Implementation of multilayer perceptron: Dive into the implementation of a multilayer perceptron, one of the foundational architectures in deep learning.

  4. Lab-4: Backpropagation: Explore the essential concept of backpropagation, a key algorithm for training neural networks.

  5. Lab-5: Optimization: Study various optimization techniques used in deep learning to improve training efficiency.

  6. Lab-6: Hyperparameters Tuning: Understand the importance of hyperparameter tuning and how it impacts model performance.

  7. Lab-7: Implementation of CNNs: Delve into Convolutional Neural Networks (CNNs) and learn to implement them.

  8. Lab-8: Implementation of famous CNN architectures: Implement well-known CNN architectures like ResNet and VGG Net.

  9. Lab-9: Image Segmentation using neural networks: Learn how to perform image segmentation using neural networks.

  10. Lab-10: Implementation of RNNs: Explore Recurrent Neural Networks (RNNs) and implement them for various tasks.

  11. Lab-11: Introduction to NLP: Get introduced to Natural Language Processing (NLP) and its applications in deep learning.

  12. Lab-12: Applications of RNNs: Apply RNNs to real-world problems and understand their versatility.

Getting Started

Each lab is contained within its respective directory and includes instructions and code related to the specific experiment. To get started with a lab, navigate to its directory and open the lab files. Each lab is self-explanatory.

Prerequisites

Before attempting the labs, ensure you have a basic understanding of deep learning concepts and Python programming. You might find it helpful to review relevant course materials and lecture notes.

Acknowledgments

I would like to express my gratitude to the faculty and instructors at NUST for their guidance and support throughout the CS405 Deep Learning course.

Happy learning and exploring the world of deep learning!