https://github.com/nikoshet/new-york-city-taxi-fare-prediction-machine-learning

Project for course 'Machine Learning' for M.Sc. 'Data Science and Machine Learning' in NTUA
https://github.com/nikoshet/new-york-city-taxi-fare-prediction-machine-learning

data-science keras-tensorflow machine-learning numpy pandas python

Last synced: about 2 months ago
JSON representation

Project for course 'Machine Learning' for M.Sc. 'Data Science and Machine Learning' in NTUA

• Host: GitHub
• URL: https://github.com/nikoshet/new-york-city-taxi-fare-prediction-machine-learning
• Owner: nikoshet
• License: gpl-3.0
• Created: 2020-03-11T13:11:28.000Z (almost 5 years ago)
• Default Branch: master
• Last Pushed: 2020-03-19T13:15:16.000Z (almost 5 years ago)
• Last Synced: 2024-04-19T19:08:01.331Z (8 months ago)
• Topics: data-science, keras-tensorflow, machine-learning, numpy, pandas, python
• Language: Jupyter Notebook
• Homepage:
• Size: 2.18 MB
• Stars: 6
• Watchers: 2
• Forks: 1
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

README

        
# Machine Learning M.Sc. Course Project

Dataset: "New York City Taxi Fare Prediction" (Kaggle).

More can be found [here](https://www.kaggle.com/c/new-york-city-taxi-fare-prediction/)

## Contributors

[Nick Nikitas](https://github.com/nikoshet) 

[Filippos Markolefas](https://github.com/filippos93)

[Myron Sampsakis](https://github.com/sbmyron)

## Notebook Structure

```

~/Machine_Learning_Project.ipynb

│

└── Connection With Kaggle

│

└── Load Dataset

│

└── Preprocessng

   | Feature Extraction

   | Clean Data

       | General

       | Geospatial Data

│

└── Exploratory Data Analysis

   | General Analysis

   | Feature Interaction

   | Plots

│

└── Machine Learning

   | Split Data Into Train, Test set

   | Functions

   | Algorithms

       | Linear Regression

       | Random Forest

       | Epsilon-Support Vector Regression

       | XGBoost

       | Voting Regressor

       | Bagging Regressor

       | Histogram-based Gradient Boosting Regression Tree

       | Neural Network

   | Results

```

(The files JFK2.txt, LaGuardia2.txt, Manhattan.txt, Newark2.txt contain the coordinates for the NYC airports and Manhattan)

## Libraries Used

pandas, numpy, matplotlib, seaborn, shapely, sklearn, keras

### Licence

Copyright © 2020 Nick Nikitas, Filippos Markolefas, Myron Sampsakis