RGWML (an AI, Data Science & Machine Learning Library designed to minimize developer cognitive load)

This library simplifies Data Science, Machine Learning, and Artifical Intelligence operations. It's designed to leverage the best features of RUST, in a manner that is graceful, elegant, and ticklishly fun to build upon.

Modules Overview

df_utils

• Purpose: Replicate Python Pandas library functionality in Rust.
• Features: The Query and Grouper structs ease data manipulation, transformation, filtering, sorting, and aggregation.

ai_utils

• Purpose: Leverage Rust's concurrency for AI/Graph Theory based analysis.
• Features: Perform complex data analyses and process neural associations in parallel, harnessing Rust's performance and safety.

api_utils

• Purpose: Gracefully make and cache API calls.
• Features: The ApiCallBuilder struct allows you to make, cache API calls, and also manage the subsequent cached usage.

csv_utils

• Purpose: Gracefully build csv files.
• Features: The CsvBuilder struct allows you to create CSV files with grace by chaining easy-to-read methods to set headers and add rows.