Data Science Interview Practice

This repository contains code for practicing data science interview questions, adapted from resources provided by Deep ML.

Overview

The code includes exercises and solutions covering various data science topics such as:

• Machine Learning
• Linear Algebra

Folder Structure

To enhance structured learning, I have created separate folders for different Machine Learning algorithms, implemented from scratch. Each folder contains:

• A .py file with the full implementation of the ML algorithm.
• A train.py file that serves as the calling function to run the algorithm.

References

The ML algorithms have been adapted and referenced from the following sources:

• YouTube Playlist: Machine Learning From Scratch
• GitHub Repository: AssemblyAI-Community ML From Scratch

Resources

All practice content is inspired by Deep ML, a valuable resource for data science interview preparation.

License

Feel free to use the code in this repository under the MIT License.