100 Terminologies Every Machine Learning Engineer Must Master

In the exciting field of machine learning, knowing the terminology is super important, whether you’re just starting out or you’ve been doing it for a while. This blog is here to help, introducing you to 100 essential machine learning terms.

Here’s a list of 100 machine learning terminologies that are essential for every machine learning engineer to be familiar with:

1. Algorithm: A set of rules or steps used for solving a particular problem.
2. Artificial Intelligence (AI): The broad field of computer science focused on creating machines that can perform tasks requiring human intelligence.
3. Batch Learning: Training a model using the entire dataset at once.
4. Bias: Systematic error introduced by a model that consistently skews predictions in one direction.
5. Big Data: Extremely large and complex datasets that traditional data processing tools are inadequate to handle.
6. Classification: Assigning a label or category to input data.
7. Clustering: Grouping similar data points together.
8. Convolutional Neural Network (CNN): A type of neural network particularly well-suited for image processing.
9. Cross-validation: Dividing a dataset into…