💻 DS learning repository

This repository contains a collection of beginner-friendly DS projects, created purely for learning purposes.

Each .ipynb file represents an independent project.

How to run

Make sure you have all the necessary libraries (listed in the import section of each notebook).
Install any missing library using either of the following:
- In Jupyter Notebook:
```
!pip install <library_name>
```
- In Command Prompt / Termunal:
```
pip install <library_name>
```

Note: When loading datasets, remember to adjust the file paths according to your local directory structure.

Name		Name	Last commit message	Last commit date
data		data
BlackFriday_sales_prediction.ipynb		BlackFriday_sales_prediction.ipynb
Dogs_vs_Cats_image_classification.ipynb		Dogs_vs_Cats_image_classification.ipynb
Energy_consumption_prediction.ipynb		Energy_consumption_prediction.ipynb
MNIST_digit_classification.ipynb		MNIST_digit_classification.ipynb
Mini_projects.ipynb		Mini_projects.ipynb
README.md		README.md
Twitter_sentiment_analysis.ipynb		Twitter_sentiment_analysis.ipynb
Wine_quality_prediction.ipynb		Wine_quality_prediction.ipynb