Deep Learning

Deep Learning is a subfield of machine learning that focuses on neural network, a more advanced way to learn from data. Traditional machine learning relies on feature a data has, the feature are typically extracted manual by machine learning practicioner. Neural network, in high level, can learn hierarchical representations of the data, automatically extracting useful features or detecting pattern from raw input without needing for manual feature engineering.

Deep learning is suited for task which uses complex data that is hard to describe by humans such as images. As long as we can turn it into numbers, the model will learn the pattern of the number and make prediction.

All pages

• Deep Learning Foundation
• Deep Learning Tasks
• Neural Network
• CNN
• ResNet
• U-Net
• Siamese Network
• RNN
• LSTM
• GRU
• Autoencoder
• Variational Autoencoder
• GAN
• Transformers
  • Attention Mechanism
  • Transformers Architecture
  • Transformers Audio
  • BERT
  • GPT
  • BART
  • Vision Transformers
• Diffusion Model
• Reinforcement Learning
  • Reinforcement Learning Fundamental
  • Model-Based
    • Markov Models
    • Markov Decision Process
  • Model-Free
    • Monte Carlo Method
    • Temporal Difference
    • SARSA
    • Q-Learning
    • Policy Gradient
    • Imitation Learning
  • Multi-Agent