Datahack by IIT G in collab with GFG

This project demonstrates a complete pipeline for a machine learning task, including data loading, preprocessing, model training, evaluation, and submission generation. The primary objective is to predict the labels for a given test dataset based on the provided training dataset.

Table of Contents

Project Structure Requirements Data

Steps

1. Data Loading and Exploration
2. Data Preprocessing
3. Model Training and Evaluation
4. Generating Submission

Project Structure

The project includes the following files:

training_set_features.csv: Training features. training_set_labels.csv: Training labels. test_set_features.csv: Test features. submission_format.csv: Submission format. main.py: Main script containing the entire pipeline. README.md: This readme file.

Requirements

Ensure you have the following Python libraries installed:

pandas numpy scikit-learn joblib

You can install them using:

pip install pandas numpy scikit-learn joblib

The datasets are provided as CSV files:

training_set_features.csv: Contains the features for training.

training_set_labels.csv: Contains the corresponding labels for training.

test_set_features.csv: Contains the features for testing.

submission_format.csv: Provides the format for the submission file.