N

normalization

Meet Jane

Less boilerplate. More flow. Zero‑side‑effect normalization and validation helpers for JavaScript.

Jane is a small, clarity‑first helper library for normalizing, validating, and safely parsing unknown input in JavaScript and TypeScript. It’s built for developers who want predictable behavior, composable pipelines, and zero surprises — without schema systems, decorators, or framework lock‑in.

Jane is intentionally small. Intentionally explicit. Intentionally boring in all the right ways.

This is a study project built using FastAPI to practice microservice architecture, data normalization techniques, and clean API design.

The service receives raw payloads from different simulated sources and transforms them into a standardized and validated structure.

It centralizes normalization logic and demonstrates how to build a scalable, maintainable, and test-friendly data processing layer.

Several tools for audio manipulation

Python package to normalize text for speech-language models using different libraries.

An Open Educational Resource (OER) to refresh prior knowledge about functional dependencies (FDs) and normalization of relational database schemata.

Multiple Regression is almost like Simple Linear Regression, but with more than a single independent feature, which means we try to predict a value based on more than one variable.

check this project article on medium: https://medium.com/@alhendyrenad/build-a-multiple-linear-regression-model-using-python-c4d9f9cf4cc7

Grocery shopping app

This is a Collaborative-Based Movie Recommendation System developed using methods of weighted_average and Normalization(MinMaxScaling()) of Average Rating and Popularity values.

Forward-slash normalization of function results via composition