https://github.com/patilni3/project_machine_learning
Fake Currency Detection using Logistic Regression Algorithm
https://github.com/patilni3/project_machine_learning
Last synced: 5 months ago
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Fake Currency Detection using Logistic Regression Algorithm
- Host: GitHub
- URL: https://github.com/patilni3/project_machine_learning
- Owner: PatilNi3
- Created: 2022-10-31T16:52:32.000Z (over 2 years ago)
- Default Branch: main
- Last Pushed: 2022-11-08T16:54:53.000Z (over 2 years ago)
- Last Synced: 2024-07-21T10:53:29.443Z (10 months ago)
- Language: Jupyter Notebook
- Size: 471 KB
- Stars: 5
- Watchers: 1
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Machine-Learning-Project
Fake Currency Detection using Logistic Regression Algorithm
## About:
Fake Currency Detection is a real problem for both individuals and businesses. Some are constantly finding new methods and techniques to produce counterfeit banknotes, which are essentially indistinguishable from real money. Atleast for human eyes.
### So by using Machine Learning Algorithm we can find this out.
## Dataset:
data_banknote_authentication.txt
## Algorithm Used:
### Logistic Regression
## Library & Packages used:
• Pandas
• NumPy
• seaborn
• sklearn
• matplotlib
## Steps involved in the Project:
1. Reading dataset and assigning column names.
2. Data exploration - checking for missing values.
3. Checking the behaviour of data using pairplot.
4. Data processing - balancing the imbalanced data using imblearn.
5. Split the data to train and test the model.
6. Creating a ml model and trained it.
7. Model validation using Confusion Matrix.
8. Finally Prediction
# Thank You.☻