Algorithm: An algorithm is a set of well-defined instructions or procedures that are run on data to perform specific tasks. It can be described using math and pseudocode, and can be implemented with any one of a range of modern programming languages. Examples of algorithms include sorting algorithms like bubble sort, and search algorithms like best-first.
Programming: Traditional programming is a manual process where a person (programmer) creates the program. This involves formulating or coding rules based on the programmer’s knowledge and understanding of the problem. A computer program is a compiled form of human redable code which then executes based on the OS and build of the machine known has machine language. Programming is a step by step instruction given to a computer. Outcome of a program is deterministic.
Machine Learning Model: A machine learning model is an output of a machine learning algorithm, and it comprises of model data and a prediction algorithm. Machine learning algorithms perform automatic programming, where the models represent the programs. These models learn from data, or are “fit” on a dataset. Examples of machine learning algorithms include Linear Regression, Logistic Regression, Decision Tree, Artificial Neural Network, k-Nearest Neighbors, and k-Means.
In summary, an algorithm is a set of instructions used to perform a task, programming is the process of creating these instructions, and a machine learning model is the result of running a machine learning algorithm on data.
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