Machine learning is about constructing algorithms that can approximate complex functions from observations of input/output pairs. Machine learning is related to Statistics since it is trying to make predictions.
Examples of such functions include:
- Image classification
- Time-series prediction
- Language modeling
Backlinks
- NLP
- Neural networks
- Data representation
- Kernel Methods
- Why programming is a good medium for expressing poorly understood and sloppily-formulated ideas
- Gaussian Processes
- Federated learning
- Talk: Artificial Intelligence: A Guide for Thinking Humans
- Adversarial examples
- Meta-learning
- Recurrent neural networks
- Supervised learning
- Alternative learning mechanisms
- Privacy-preserving machine learning
- Computer vision
- Neural network training
- Reinforcement learning
- Reservoir computing
- Talk: Differentiation of black-box combinatorial solvers