Question - Difference between AI, ML, and DL?
Answer -
Below is the difference between AI, ML, and DL:
Artificial Intelligence: AI consists of the algorithms and techniques that enable a machine to perform the tasks commonly associated with human intelligence. The AI applications are trained to process large amounts of complex information and right decisions without human intervention. Some of the popular examples of AI applications are chatbots, Autonomous Vehicles, Space rovers, and Simulators for mathematical and scientific purposes.
Machine Learning: Machine Learning is a subset of Artificial Intelligence and is mainly used to improve computer programs through experience and training on different models. There are three main methods of Machine Learning:
- Supervised Learning: In supervised learning, the machine gets the input for twitch the output is already known. After the processing is completed, the algorithm compared the output produced from the original output and measure the degree of errors in it.
- Unsupervised Learning: Here, the instructor has no output or historical labels for the input data. So, the algorithm is expected to figure out the right path and extract the features from the given dataset. The goal is to allow the algorithm to search the data and s some structure in it.
- Reinforcement Learning: In this method of learning there are three components, the agent, environment, and actions. An agent is a decision-maker whose goal is to choose the right actions and maximize the expected reward within a set timeframe. Reinforcement learning is mainly used in robotics where the machine learns about the environment through trial and error.
Deep Learning: In Machine Learning, where the model tends to surrender to environmental changes, Deep Learning adapts to the changes by updating the models based on constant feedback. It’s facilitated by Artificial Neural Networks that mimic the cognitive behavior of the human brain.