Introduction
Wikipedia guide
The documentation for this project was created using mdBook (the documentation for mdBook can be found on its official GitHub page). The development process was divided into chapters, which you can navigate through either the table of contents or by using the left and right arrow keys on your keyboard.
The toolbar at the top of the page contains four different buttons:
- Toggle the table of contents
- Change the page's color theme
- Search for a specific word throughout the document (Shortcut: key 's')
- Print the entire book
Obs: The whole code for this wikipedia is also located inside the project's github repository.
Focus of the Project
This project focuses on the field of machine learning, specifically in the context of Airbnb. The objective was to create a model that can predict the daily rental price for Airbnb properties.
We explored various types of machine learning algorithms, considering supervised, unsupervised, and reinforcement learning. For this project, we chose to implement supervised learning with a focus on regression as it was most suitable for our dataset and objectives.
Machine Learning Considerations
During the development process, we took care to ensure the model was robust and generalizable. One of the main challenges in machine learning is overfitting, where a model becomes too tailored to the training data, resulting in poor performance on new, unseen data. To mitigate this risk, we employed several data treatment techniques that will be seen in the following chapters.
By incorporating these precautions, we aimed to create a model that not only performed well on the training set but also demonstrated strong generalization capabilities when applied to real-world data.