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Machine learning model using logistic regression to classify the Iris-Flower of dataset.

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Iris-Flower Machine Learning Model

This is a Machine Learning model wich the classic case of Iris-Flower dataset was used. This model aims to learning and reproduce the results of sums of all characteristics of Iris-Flowers and use it to classification of some Iris-Flower type.

🔧 Tools

  • Python: Is a high-level, versatile, and interpreted programming language known for its simplicity and readability.

  • Jupyter Notebook: Is an open-source web application that allows you to create and share documents that contain live code, equations, visualizations, and narrative text. It is widely used in data science, scientific research, machine learning, and other fields where interactive computing and data exploration are important.

  • Pandas: Is a software library written for the Python programming language for data manipulation and analysis.

  • Numpy: Is a library for the Python programming language, adding support for large, multi-dimensional arrays and matrices, along with a large collection of high-level mathematical functions to operate on these arrays

  • Scikit-Learn: Is a free software machine learning library for the Python programming language.

⚙️ How It Works

  • When you run the program, you will receive some inputs in your screen.
  • The first input will ask you about the sepal.
  • The second input will ask you about the sepal width.
  • The third input will ask you about the petal length.
  • The fourth input will ask you about the petal width.
  • At the end of this session, the program will show you the final result and will ask you if you want to made another some case.

💻 How To Run

  • This is a Jupyter Notebook algorithm.
  • I recommend that you run this algorithm on a Jupyter notebook environment in your machine or browser.
  • But you can run it on your terminal if you have Python on your computer.
    • In your terminal, go at the path were your save the files.
    • Run (python IrisFlower_ML)