https://github.com/a19xys/dm-csgo_analysis

Analysis to address the most important aspects of the knowledge discovery process from data.
https://github.com/a19xys/dm-csgo_analysis

data-analysis data-mining data-science dataset jupyter-notebook python

Last synced: about 1 month ago
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Analysis to address the most important aspects of the knowledge discovery process from data.

• Host: GitHub
• URL: https://github.com/a19xys/dm-csgo_analysis
• Owner: a19xys
• License: gpl-3.0
• Created: 2025-04-04T04:26:41.000Z (about 1 year ago)
• Default Branch: main
• Last Pushed: 2025-04-04T04:56:10.000Z (about 1 year ago)
• Last Synced: 2025-04-04T05:25:33.376Z (about 1 year ago)
• Topics: data-analysis, data-mining, data-science, dataset, jupyter-notebook, python
• Language: Jupyter Notebook
• Homepage:
• Size: 0 Bytes
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

          
# Dataset analysis for knowledge discovery

This analysis will address some of the most important aspects of the knowledge discovery process from data, including:

- Data storage and loading

- Exploratory data analysis

- Data preprocessing

- Model validation

To achieve this goal, we will manipulate and visualize the data using various functions in the Plotly library. We will also use classification algorithms such as decision trees using the Scikit-learn library.

Our goal will be to load, explore, and prepare our data, learn and validate different classification models, and be able to interpret the results. To achieve this, we will use the following dataset:

- `csgo`: https://www.kaggle.com/datasets/christianlillelund/csgo-round-winner-classification