https://github.com/s-rb/ml_usdrateprediction

Skillbox Python DataScience Intensive
https://github.com/s-rb/ml_usdrateprediction

Last synced: 24 days ago
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Skillbox Python DataScience Intensive

• Host: GitHub
• URL: https://github.com/s-rb/ml_usdrateprediction
• Owner: s-rb
• Created: 2020-03-28T06:35:32.000Z (almost 5 years ago)
• Default Branch: master
• Last Pushed: 2024-01-23T20:42:05.000Z (12 months ago)
• Last Synced: 2024-11-05T21:16:54.548Z (2 months ago)
• Language: Jupyter Notebook
• Size: 116 KB
• Stars: 1
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# ML_UsdRatePrediction

Skillbox Python DataScience Intensive

![Python](https://img.shields.io/badge/-Python-05122A?style=flat&logo=Python&logoColor=fffffb) ![Pandas](https://img.shields.io/badge/-Pandas-05122A?style=flat&logo=Pandas) ![MathPlotLib](https://img.shields.io/badge/-MathPlotLib-05122A?style=flat&logo=MathPlotLib) ![Scikit-learn](https://img.shields.io/badge/-Scikit_learn-05122A?style=flat&logo=sklearn)

Skillbox DataScience training intensive "Predicting the dollar exchange rate" using Python.

Prediction is made based on historical data.

Libraries used:

- Pandas - for getting data from an Excel file,

- MathPlotLib for plotting.

- Scikit-learn (SKLearn) for algorithms/

The mean absolute error (mean_absolute_error from sklearn.metrics) was used for evaluation.

Algorithms:

- LinearRegression,

- KNeighborsRegressor,

- MLPRegressor,

- RandomForestRegressor,

Automation of parameter selection and cross-validation:

- GridSearchCV from sklearn.model_selection