Index of Questions that can be answered by AI broadly and are being applied in various sectors. Broadly AI helps answer 5 problem areas
Is this A or B ?
Is this Weird ?
How much ? How many ?
How is this organised ?
What should I do now ?
Machine learning is a large field of study that overlaps with and inherits ideas from many related fields such as artificial intelligence.
The focus of the field is learning, that is, acquiring skills or knowledge from experience. Most commonly, this means synthesizing useful concepts from historical data.
As such, there are many different types of learning that you may encounter as a practitioner in the field of machine learning: from whole fields of study to specific techniques.
Fields of study, such as supervised, unsupervised, and reinforcement learning.
Hybrid types of learning, such as semi-supervised and self-supervised learning.
Broad techniques, such as active, online, and transfer learning.
1. Is this A or B ? Classification Algorithms
e.g.
2. Is this Weird ? Minority in Voluminous Data - Anomaly Detection Algorithms
Define a single class(large pool of good data) - universe of acceptance vs bad
e.g. Fraud transactions
3. How much ? How many ? - Regression Algorithms
e.g. Temperature, Climate [Predict Numbers]
4. How is this organised ? - Clustering Algorithms
e.g. Customer Personas, Netflix categories, Spotify playlists
5. What should I do now ? - Reinforcement learning algorithms
e.g. Autonomous driving, amazon dynamic pricing, user personalisation. The training is very complicated [requires many different use cases]
Well that’s one for a self-driving car..literally….
Reference Images to breakdown the broad field of ML/AI
Example of ML/AI Application areas..
