Instagram Giveaway Comment Analysis & Product Restocking Prediction

Project 1: Instagram Giveaway Comment Analysis for BolaPsd

Overview

This project aims to analyze comments from an Instagram post exported to a CSV file to determine the winner of a giveaway competition. The primary goal is to identify the comment with the highest count.

Files

• result.csv: CSV file containing the exported comments from the Instagram post.
• psd.ipynb: Jupyter Notebook containing the Python code for analyzing comments.

Usage

1. Ensure you have Python installed on your system.
2. Install the required dependencies
3. Run the Jupyter Notebook psd.ipynb to execute the analysis code.

Results

The analysis will identify the comment with the highest count, which can be considered the winner of the giveaway competition.

Project 2: Product Restocking Prediction with Machine Learning for Bola Psd

Overview

This project utilizes datasets containing information on all products sold by Bolapsd, including sizes and quantities sold. The data is cleaned to retain only relevant information. A linear regression model is trained based on this data to predict the sizes and respective quantities of T-shirts to restock.

Files

• inventory sales.csv: CSV file containing sales data including product information, sizes, and quantities sold.
• size model.ipynb: Jupyter Notebook containing the Python code for training the linear regression model and making predictions.

Usage

1. Ensure you have Python installed on your system.
2. Install the required dependencies
3. Run the Jupyter Notebook size model.ipynb to train the model and make predictions.

Results

The trained linear regression model can predict the sizes and quantities of T-shirts to restock based on the desired restocking amount.