https://github.com/redflag-bugs/datahack
https://github.com/redflag-bugs/datahack
Last synced: about 2 months ago
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- Host: GitHub
- URL: https://github.com/redflag-bugs/datahack
- Owner: REDFLAG-bugs
- Created: 2024-06-17T17:41:42.000Z (almost 2 years ago)
- Default Branch: main
- Last Pushed: 2025-01-10T10:17:38.000Z (over 1 year ago)
- Last Synced: 2025-03-21T03:31:10.989Z (about 1 year ago)
- Language: Jupyter Notebook
- Size: 13.4 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# 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.