Understanding AI is crucial. Here's a quick look at its main areas:
π€ Artificial Intelligence
- π
Planning and Scheduling
- π£οΈ Natural Language Processing (NLP)
- ποΈ Computer Vision
- π§ Knowledge Representation
- ποΈ Speech Recognition
- βοΈ AI Ethics
- 𧩠Cognitive Computing
π€ Machine Learning
- π Dimensionality Reduction
- π³ Decision Trees
- πΌ Support Vector Machines (SVM)
- π€ Ensemble Learning
- π§ Feature Engineering
π€ Neural Networks
- βοΈ Perceptrons
- πΌοΈ Convolutional Neural Networks (CNNs)
- π Long Short-Term Memory (LSTM)
- πΈοΈ Multi-Layer Perceptron (MLP)
- 𧩠Backpropagation
π€ Deep Learning
- π Deep Neural Networks (DNNs)
- π₯οΈ Deep Convolutional Neural Networks (CNNs)
- πΉοΈ Deep Reinforcement Learning
- π¦ Capsule Networks
π€ Generative AI
- π Language Modeling
- π Transfer Learning
- π§ Transformer Architecture
- π― Self-Attention Mechanism
- π£οΈ Natural Language Understanding
- π Summarization
- π¬ Dialogue Systems
If you found this overview useful, drop a π!
Source: Brij Kishore Pandey (@brijpandeyji)