Welcome to the Introduction to Neural Networks course! This page provides an overview of the course content and objectives.

Course Outline

  • Module 1: Introduction to Neural Networks

    • What are Neural Networks?
    • History and Evolution
    • Types of Neural Networks

  • Module 2: Basic Concepts

    • Activation Functions
    • Backpropagation
    • Loss Functions

  • Module 3: Deep Learning

    • Convolutional Neural Networks (CNNs)
    • Recurrent Neural Networks (RNNs)
    • Generative Adversarial Networks (GANs)

  • Module 4: Practical Applications

    • Image Recognition
    • Natural Language Processing
    • Time Series Analysis

  • Module 5: Advanced Topics

    • Transfer Learning
    • Autoencoders
    • Reinforcement Learning

Learning Objectives

  • Understand the fundamental concepts of Neural Networks.
  • Learn about different types of Neural Networks and their applications.
  • Gain hands-on experience in building and training Neural Networks.
  • Explore advanced topics in Deep Learning.

Resources

For further reading, you may visit our Deep Learning Resources page.

Neural_Networks