Machine learning is a method of data analysis that automates analytical model building. It is a branch of artificial intelligence based on the idea that systems can learn from data, identify patterns and make decisions with minimal human intervention. Machine learning involves computers discovering how they can perform tasks without being explicitly programmed.
For example, medical diagnosis, image processing, prediction, classification, learning association, regression etc.
Machine learning is used in internet search engines, email filters to sort out spam, websites to make personalized recommendations, banking software to detect unusual transactions, and lots of apps on our phones such as voice recognition.
Device machine learning features, like object detection in images and video, language analysis, and sound classification.
Vision- Build features that can process and analyze images and video using computer vision.
Natural Language- Process and make sense of text in different ways, like embedding or classifying words.
Speech- Take advantage of speech recognition and saliency features for a variety of languages.
Sound- Analyze audio and recognize it as a particular type, such as laughter or applause.
There are 14 types of learning which are familiar with machine learning, they are,
1. Supervised Learning
2. Unsupervised Learning
3. Reinforcement Learning
4. Semi-Supervised Learning
5. Self-Supervised Learning
6. Multi-Instance Learning
7. Inductive Learning
8. Deductive Inference
9. Transductive Learning
10. Multi-Task Learning
11. Active Learning
12. Online Learning
13. Transfer Learning
14. Ensemble Learning