What it does
IRIS-CLASSIFICATION: In this project we Trained a model to distinguish between different species of the Iris flower based on four measurements: sepal length, sepal width, petal length, and petal width.
How we built it
This project is based on Deep Learning and we built it in Google Colab. We used libraries such as Tensorflow, NumPy, Seaborn, Panda, Matplotlib etc.
Challenges we ran into
The hardest task is to get a good accuracy, and we took the challenge to achieve a good accuracy. First we calculated this model's accuracy mannually which is 86.61% then we again calculated it by using logic regression and cross validation.
Accomplishments that we're proud of
we're proud the we successfully tackled the challenge and finally we achieved the final Accuracy of the model is: 98.18%
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