Artificial Intelligence, Machine Learning and Deep Learning
These are some commonly used terms which are frankly a little confusing. They all seem to have the same meaning and seem interchangeable but it doesn’t make sense why there must be different words with the same meaning. So, I studied into this a little and here is what I found:
-AI stands for Artificial intelligence, where intelligence is defined as the ability to acquire and apply knowledge.
-AI completely deals with Structured, semi-structured, and unstructured data.
-The goal of AI is to make a computer system as smart as humans so that it can solve complex problems.
-AI is for decision making.
-The aim is to increase the chance of success and not accuracy.
-AI is for finding the optimal solution. It includes learning, reasoning, and self-correction.
-AI tries to simulate natural intelligence to solve complex problems.
-In short, AI leads to intelligence or wisdom.
-Machine Learning is defined as the acquisition of knowledge or skill.
-Machine learning is a subset of Artificial Intelligence.
-Machine learning deals with Structured and semi-structured data.
-The goal is to learn from data on a certain task for maximizing the performance of the machine on this task.
-It is used to create machines that can perform only those specific tasks for which they are trained.
-The aim is to increase accuracy, but it does not care about success.
-ML will go for a solution without factoring in how optimal it is.
-ML allows the system to learn new things from data.
-In short, ML leads to knowledge.
-Deep Learning is a subset of machine learning.
-It technically is machine learning and functions in the same way but has different capabilities
-In deep learning, algorithms are created and function similar to machine learning, but there are many levels of these algorithms, each providing a different interpretation of the data it conveys. This network of algorithms is called artificial neural networks. In simple words, it resembles the neural connections that exist in the human brain.
-The main difference between deep and machine learning is, machine learning models become better progressively but the model still needs some guidance from the programmer but in the case of deep learning, the model does that by itself.
-The main advantage of deep learning is that it doesn’t necessarily need structured data.
-Machine learning algorithms almost always require structured data, while deep learning networks rely on layers of ANN (artificial neural networks).