Welcome to the introduction to Deep Learning 101! If you're new to the field or looking to expand your knowledge, this course is designed to provide a comprehensive overview of deep learning concepts, techniques, and applications.

Course Outline

  • Introduction to Deep Learning

    • What is Deep Learning?
    • History and Evolution
    • Key Components

  • Neural Networks

    • Basic Neural Network Structure
    • Activation Functions
    • Backpropagation

  • Convolutional Neural Networks (CNNs)

    • Understanding CNNs
    • Applications in Image Recognition
    • CNN Architecture

  • Recurrent Neural Networks (RNNs)

    • Overview of RNNs
    • Types of RNNs
    • Applications in Natural Language Processing

  • Deep Learning Frameworks

    • TensorFlow
    • PyTorch
    • Keras

  • Practical Deep Learning Projects

    • Image Classification
    • Object Detection
    • Natural Language Processing

Learning Resources

For further reading and resources, check out our Deep Learning Tutorial.

Images

  • Deep Learning Concept
  • Neural Network Structure
  • CNN Architecture
  • RNN Types
  • Deep Learning Frameworks