Machine learning is a subset of artificial intelligence (AI) that focuses on the development of algorithms that can learn from and make predictions or decisions based on data.
Key Concepts
- Supervised Learning: Algorithms learn from labeled training data.
- Unsupervised Learning: Algorithms find patterns in data without labels.
- Reinforcement Learning: Algorithms learn from interactions with the environment.
Learning Resources
- Machine Learning Crash Course - A free course offered by Google.
- Machine Learning Yearning - A free online book by Andrew Ng.
Practical Examples
- Image Recognition: Identifying objects in images.
- Speech Recognition: Transcribing speech to text.
- Medical Diagnosis: Predicting diseases based on patient data.
Machine Learning in Action
Further Reading
- Deep Learning - A comprehensive book on deep learning by Ian Goodfellow, Yoshua Bengio, and Aaron Courville.
- Pattern Recognition and Machine Learning - A book on pattern recognition and machine learning by Christopher Bishop.
Pattern Recognition and Machine Learning