Tech stack used:
- Python => 3.10.6
- Jupyter Notebook => 6.4.12
- Tensorflow => 2.11.0
- Keras =>
- BeautifulSoup => 4.12.1
- Numpy => 1.23.2
- Seaborn => 0.12.1
- Matplotlib => 3.5.3
- Pandas => 1.4.4
- StatsModel => 0.13.2
To download, open Pycharm and use Python manager called pip:
pip install <PACKAGE_NAME>
Optional you could use below command to get specific version:
pip install <PACKAGE_NAME>==<VERSION_NUMBER>
Python scripts developed to perform analysis on Volkswagen car prices. The data was scrapped from the popular Polish website OtoMoto (https://www.otomoto.pl/) using Beautiful Soup Python library. Whole project is going to be based on Recurrent Neural Networks (casual RNN).
Whole project description could be found in folder: "project_report(in_Polish)".
But as name can suggest it is written in Polish. Basically it's a report which was created as a part of
AI classes at university.
In short, title translation of each subpoint:
"
- Description of the problem and data
- Data preprocessing
- Description of the applied neural networks
- Discussion of results and conclusions "
Maybe in the future there will be finished "hyperparameters tunning", no time to fix it now - doesn't work properly.
Literature describing the concept of hyperparameters tunning:
- https://www.analyticsvidhya.com/blog/2022/02/a-comprehensive-guide-on-hyperparameter-tuning-and-its-techniques/
- https://towardsdatascience.com/hyperparameter-tuning-in-python-21a76794a1f7
- https://scikit-learn.org/stable/modules/grid_search.html
- [Szymon Rogowski] (https://github.com/PsimonL)
- [Piotr Sobol] (https://github.com/Pyother)
AGH University of Science and Technology in Kraków, Poland
Industrial Computer Science, Computational Engineering students at WIMIIP faculty, 6th term - Bachelor's degree in Engineering (Technical Informatics and Telecommunications).