podysseas/inside_airbnb-athens

The main objective of this project is to create machine learning models that predicts the price of apartment listings , given its attributes.

I. Introduction:

Project Overview:

The main objective of this project is to make a model that predicts the price of a listing, given its attributes. Several subtasks can be spawned from this objective. The main categories are:

● Explore the given data. See what they describe and gather valuable insights about their properties.

● Preprocess the data so that they can be used for predicting the listing price.

● Model the data through the sklearn estimators or Azure services

Dataset:

The dataset is provided in a file called listings.csv and contains nominal information about the listings, like its neighbourhood, its description, amenities, bedrooms, bathrooms and more.

II. Software Requirements:

This project requires Python 3.7 and the following Python libraries installed:

• Python 3.7
• NumPy, Pandas , matplotlib
• scikit-learn

Installation

1. Clone this repository.
2. Install Python 3.7 or older versions
3. Ensure all libraries are installed using pip install <library> --user

III. Project Architecture:

This repository azureai-2021-team1 includes 1 main directory and 4 Notebooks:

III-1. Directories:

- help_functions: A directory conaints supportive functions

III-2. Notebooks:

- Deliverable01.ipynb: A notebook containing the answers to the aforementioned questions about EDA

- Deliverable02.ipynb: A notebook containing extra EDA

- Deliverable03.ipynb: A notebook showing the preprocessing steps

- Deliverable04.ipynb: A notebook containing the production-level code

Authors

• jvario,podysseas,vmoulop,katerpont & antonesgiouris - Initial work - jvario -podysseas -vmoulop -katerpont -antonesgiouris

License

This project is licensed under the MIT License - see the LICENSE file for details