This was a Major Project developed by a 4 Member Team at my Engineering College at Hyderabad, India. We had throughly used commonly available Datasets from Kaggle for Different Sepal Length,Sepal Width Petal Length and Petal Width datasets that were commonly available ready-made to use and train the model.

Libraries Used:- pandas- For converting regular Dataframe into Columns for better visualization of data. Scikit-Learn Library- This library further consists of Modules like: _"load_iris" _(Loads the Iris Dataset) "train_test_split" (Splits the available data set into Training and Testing set respectively) "accuracy_score" (This is used to check whether the accuracy of the model is correct and improvements that need to be made on the model if the accuracy is less)

NOTE:- All Available A.I Tools were used during this Project's Building With also the help of a Guide appointed by the Department of A.I & M.L.

Points to keep in Mind:- -> This gives an accuraccy performance of "1.00" because the model has been trained on An Pre-Existing/Pre- Defined Dataset from Kaggle. -> When these kind of Pre-Defined Datasets are used the model takes random values and it does not have any error because the data has already been cleaned.