Lecture

AI and Machine Learning English Terminology

AI and machine learning are no longer technologies confined to a specific sector.

They are now widely applied across various services such as recommendation systems, chatbots, image classification, and natural language processing. As a result, having a fundamental understanding and the ability to collaborate in this field has become a necessity for almost all developers.

In the process of developing or operating AI systems, specialized concepts like model design, data preprocessing, performance evaluation, and hyperparameter tuning frequently arise. It is crucial to accurately understand and use related English expressions when sharing these concepts with team members or external partners.

In this lesson, we will compile English expressions that are frequently used in AI and machine learning projects.

Quiz
0 / 1

Which verb best describes the process of teaching an AI system using labeled data?

cluster

train

deploy

split

Lecture

AI Tutor

Design

Upload

Notes

Favorites

Help

English Expressions for AI Developers

train a model

In AI/ML, 'train' refers to the process of having the model learn from data.

We trained a model using a labeled dataset.

preprocess the data

Preprocess refers to the steps of cleaning and preparing data before model training.

We need to preprocess the data to remove noise and handle missing values.

evaluate accuracy

Evaluate means to assess, and accuracy refers to the measurement of correctness. It is a common performance metric.

We evaluated the model's accuracy on a test set.

tune hyperparameters

Hyperparameters are settings defined before the learning process, and to 'tune' means to adjust for better performance.

We tuned the hyperparameters to improve the model’s performance.

prevent overfitting

Overfitting is a phenomenon where the model is too closely tailored to the training data.

We used regularization to prevent overfitting.

deploy a model

Deploy refers to the process of applying the model in a real-world service environment.

After training, we deployed the model to production.

infer from input data

Infer is a verb meaning 'to deduce' from the given data, and it is used in prediction tasks.

The model infers the sentiment from the input text.

split data into training and test sets

To split means to divide data, and training/test set are fundamental terms in machine learning.

We split the data into training and test sets with an 80:20 ratio.

cluster unlabeled data

To cluster is a verb referring to grouping similar data together.

We used K-Means to cluster unlabeled data.

visualize model performance

Visualize means to represent data using charts, common in analysis stages.

We visualized the model performance using a confusion matrix.