Iris Dataset: Multi-class Classification using Machine Learning

In this video, we will explore a machine learning classification task using the Iris dataset🌸. 🔍 What’s Inside: 1. Loads the Iris dataset. 2. Basic understanding of Dataset 3. Exploratory Data Analysis 4. splits the dataset into features (X) and targets (Y). 5. splits the data into training and testing sets. 6. trains the classifier on the training data. 7. Predicts the classes for the test data. 8. calculates accuracy and displays a classification report. 🌐 Resources: 🌿Iris Dataset Link: https://www.kaggle.com/datasets/arshid/iris-flower-dataset 🌿Google Colab Notebook: https://github.com/AnsaBaby/Story-telling-with-Iris-Dataset/blob/main/Exploratory_Data_Analysis_of_Iris_Dataset.ipynb 🌿Medium Blog Post: https://ansababy.medium.com/story-telling-with-iris-dataset-multi-class-classification-using-machine-learning-18a8d94f681f 🌟 Enjoyed this journey through the Iris dataset? Don’t forget to like, subscribe, and hit that notification bell 🔔 to stay updated on more exciting data adventures! 🌿 📌 Connect with me: Follow me on Instagram : https://www.instagram.com/the.friendly.data.geek/ Connect with me on LinkedIn : https://www.linkedin.com/in/ansababy/ #MachineLearning,#DataScience,#RandomForest,#IrisDataset,#Classification,#FeatureEngineering,#PythonProgramming,#AI,#MLCommunity