This project requires Python 2.7 and the following Python libraries installed:
You will also need to have software installed to run and execute a Jupyter Notebook
If you do not have Python installed yet, it is highly recommended that you install the Anaconda distribution of Python, which already has the above packages and more included. Make sure that you select the Python 2.7 installer and not the Python 3.x installer.
Template code is provided in the iris_notebook.ipynb
jupyter notebook file. You will also be required to use the data.csv
dataset file to complete your work. While some code has already been implemented to get you started, you will need to implement additional functionality when requested to successfully complete the project.
In a terminal or command window, navigate to the top-level project directory iris-dataset/
(that contains this README) and run one of the following commands:
ipython iris_notebook.ipynb
or
jupyter notebook iris_notebook.ipynb
This will open the Jupyter Notebook software and project file in your browser.
The dataset used in this project is included as iris.csv
. This dataset is a freely available on the UCI Machine Learning Repository. This dataset has the following attributes:
Features
Features
: SepalLengthCm , SepalWidthCm, PetalLengthCm, PetalWidthCm
Target Variable
Target
: Species