https://github.com/hariprasath-v/machinehack-dare_in_reality_hackathon

Build a machine learning model that predicts the Envision Racing drivers’ lap times.
https://github.com/hariprasath-v/machinehack-dare_in_reality_hackathon

catboostregressor data-science exploratory-data-analysis feature-engineering gradio gradio-interface klib machine-learning numpy optuna pandas python seaborn sklearn

Last synced: 8 months ago
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Build a machine learning model that predicts the Envision Racing drivers’ lap times.

• Host: GitHub
• URL: https://github.com/hariprasath-v/machinehack-dare_in_reality_hackathon
• Owner: hariprasath-v
• License: gpl-3.0
• Created: 2021-11-29T09:23:22.000Z (almost 4 years ago)
• Default Branch: main
• Last Pushed: 2022-01-15T14:50:44.000Z (almost 4 years ago)
• Last Synced: 2025-01-13T01:44:57.097Z (9 months ago)
• Topics: catboostregressor, data-science, exploratory-data-analysis, feature-engineering, gradio, gradio-interface, klib, machine-learning, numpy, optuna, pandas, python, seaborn, sklearn
• Language: Jupyter Notebook
• Homepage:
• Size: 1.55 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

          
# Machinehack-dare_in_reality_hackathon

### Competition hosted on  MACHINEHACK 

# About

### Build a machine learning model that predicts the Envision Racing drivers’ lap times.

### Competition Public LB Rank: 97/361   & Private LB Rank: 162/352

### Evaluation Metric is RMSLE.

### File information

 * dare_in_reality_hackathon_2021_model.ipynb

    ### Packages Used,

        * Sklearn

        * catboost

        * Pandas

        * re

        * klib

        * datetime

        * Numpy

        * Matplotlib

        * gradio

        * Optuna

        * shap

        

     ### Basic Exploratory Data Analysis

     ### Created Catboost regressor model and tune the hyperparameters with the optuna framework.

     ### Model interpretation with shap     

     ### Created Demo Web-App using Gradio library

     ### Model RMSLE is: 0.22119371161605259

### Optuna Optimization History

![Alt text](https://github.com/hariprasath-v/Machinehack-dare_in_reality_hackathon/blob/main/Optuna%20Optimization%20Plot.png)

### Feature Importance     

![Alt text](https://github.com/hariprasath-v/Machinehack-dare_in_reality_hackathon/blob/main/Feature%20Importance.png)

### Hyperparameter Importance

![Alt text](https://github.com/hariprasath-v/Machinehack-dare_in_reality_hackathon/blob/main/Hyperparameter%20Importance.png)

### Demo App Screenshot.

![Alt text](https://github.com/hariprasath-v/Machinehack-dare_in_reality_hackathon/blob/main/Model_Demo_App_%20Gradio_UI.png)