A regular expression (regex) is a sequence of characters that specifies a search pattern. It is a fundamental and powerful tool used in data science and software engineering for text processing. When preparing a training dataset, a regular expression filter can be applied to a large corpus of text to efficiently select, extract, or clean data entries that contain specific keywords or conform to a particular pattern. This makes it the ideal tool for the task described.

A. ActionScript is a scripting language primarily used for developing web applications and software for the Adobe Flash Platform, not for general data preparation in machine learning.

B. A Tableau dashboard is a data visualization and business intelligence tool used for creating interactive reports, not for programmatic filtering and selection of raw training data.

C. A JSON parser is a tool for reading and interpreting data structured in JSON format. While necessary to access the data, it does not perform the keyword search itself.

1. Official Vendor Documentation (NVIDIA): The NVIDIA RAPIDS cuDF library, designed for GPU-accelerated data science, provides string methods that heavily utilize regular expressions for filtering and manipulation. For example, the StringMethods.contains function checks if a specific pattern or regex is contained within the strings of a Series.

Source: NVIDIA RAPIDS cuDF v24.04.00 documentation, cudf.core.column.string.StringMethods.contains.

2. University Courseware (Stanford University): In natural language processing (NLP) courses, regular expressions are taught as a foundational technique for processing text. They are used for tasks like tokenization and identifying specific entities, which is a form of data selection based on patterns (keywords).

Source: Jurafsky, D., & Martin, J. H. (2023). Speech and Language Processing (3rd ed.). Chapter 2: "Regular Expressions, Text Normalization, Edit Distance". (This textbook is standard courseware for Stanford's CS224N and other leading NLP courses).

3. University Courseware (University of California, Berkeley): Data science curricula introduce regular expressions as a core tool for working with text data. They are used to clean, validate, and filter data based on complex string patterns, which includes selecting lines or documents containing specific keywords.

Source: UC Berkeley, Data 100: Principles and Techniques of Data Science, Fall 2023, Lecture 10: "Text: Regex".