4Geeks Coding Projects tutorials and exercises for people learning to code or improving their coding skills
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beginnerRepository
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Bike sharing system can be a virtual sensor network that can be used for sensing mobility in a city. Hence, it is expected that most of important events in the city could be detected via monitoring these data.
In this project, practice your new Boosting Algorithm skills trying to predict the number of bike rentals in a specific city.
You will not be forking this time, please take some time to read this instructions:
Once you are finished creating your model, make sure to commit your changes, push to your repository and go to 4Geeks.com to upload the repository link.
Predicting bike rental using Boosting Algorithm
Step 1:
The dataset can be found in this project folder as 'bike_sharing_dataset.csv' file. The core data set is related to the two-year historical log corresponding to years 2011 and 2012 from Capital Bikeshare system, Washington D.C., USA which is publicly available in http://capitalbikeshare.com/system-data. You are also welcome to load it directly from the following link (https://raw.githubusercontent.com/4GeeksAcademy/random-forest-project-tutorial/main/impressions.csv
), or to download it and add it to your data/raw folder. In that case, don't forget to add the data folder to the .gitignore file.
You can find the description of each feature in the 'data-dictionary.md' file on this folder.
Time to work on it!
Step 2:
Explore and clean the data.
Step 3:
Build a first baseline model using Linear Regression. Chose an evaluation metric. Then, use a boosting algorithm and evaluate the performance of both models.
Step 4:
Use the app.py to create your pipeline.
Step 5:
To save your model and be able to use it later use the following code:
1 2import pickle 3 4filename = 'finalized_model.sav' 5pickle.dump(model, open(filename, 'wb'))
In your README file write a short summary.
4Geeks Coding Projects tutorials and exercises for people learning to code or improving their coding skills
Difficulty
beginnerRepository
Click to openVideo
Not available
Live demo
Not available
Average duration
2 hrs
Technologies