ML is a subfield of artificial intelligence and aims at building systems that are capable of performing tasks without being explicitly programmed to do so. ML algorithms employ mathematical models that learn from existing data to perform tasks such as prediction, classification, decision-making, and so on. The learning bit of the model is also called training, where the model analyzes large volumes of data to identify patterns. This process is computationally intensive as the model needs to perform numerous calculations for the given data. However, with the continual advancement in computational power at our disposal, training, and the deployment of ML models, this has become fairly easy and quite popular. Since NLP also requires that we analyze large volumes of data, ML algorithms are widely applied in terms of text processing.
ML algorithms can be divided into three categories, as shown in the following diagram:
Let's look at these in more depth:
- Supervised...
