There is no shortage of machine learning algorithms, just as Machine Learning has almost unlimited uses. It ranges from the fairly simple to the extremely complex. A few of the most commonly used models are:
Decision trees: These models use observations about certain actions and determine the most appropriate path to reach the desired result.
K-cluster: This model includes a certain number of data points in a certain number of groupings based on similar characteristics.
Neural networks: These deep learning models use large amounts of training data to identify correlations between many variables to learn to process future data.
Reinforcement learning: This area of ​​deep learning involves repeating patterns in many attempts to complete a process. Steps that produce favorable results are rewarded, and steps that produce undesirable results are penalized until the algorithm learns the optimal process.