This repository contains my learning by practice notebooks and practicals of Data Science Course.
The notebooks cover concepts from Python basics to Machine Learning, model deployment, and Generative AI. This repo is mainly created to document my learning and hands-on practice.
- Python Basics
- Statistics Fundamentals
- SQL Basics
- Machine Learning Algorithms
- Linear Regression
- Logistic Regression
- Decision Trees
- K-Means Clustering
- Model Deployment
- Neural Networks
- Generative AI
Python • Jupyter Notebook • NumPy • Pandas • Scikit-learn • SQL
This repository represents my ongoing learning process.
Some notebooks may include:
- Code implemented while following tutorials
- Experimental implementations
- Concepts that I am still exploring and improving
A few notebooks may not produce perfect results yet, and some sections will be improved as I continue learning.
⭐ Documenting my journey into Data Science through practice and exploration .
- "This implementation was followed from tutorial"
- "I am still exploring how this algorithm works internally"
- git clone https://github.com/Lakhan-cs/DS_course-oneshot.git
- pip install -r requirements.txt