Iris Classification using SVM for beginners | ML series | Video-12 | Hindi скачать в хорошем качестве

Iris Classification using SVM for beginners | ML series | Video-12 | Hindi

In this video, we take a hands-on approach to learning how to train a Support Vector Classifier (SVC) using the popular Iris dataset. The Iris dataset is a classic dataset in the field of machine learning and contains information on three different types of Iris flowers: setosa, versicolor, and virginica. We will be using the SVC algorithm from the scikit-learn library in Python to train our model and make predictions on the Iris dataset. The video covers all the necessary steps for training a SVC model, including loading the data, splitting it into training and testing sets, training the model, and evaluating its performance. The video is perfect for anyone who wants to get started with SVC and understand how it works in practice Data exploration:    • Data Exploration and Handling Missing valu...   Label encoding:    • One hot encoding & Label encoding | ML ser...   Dataset link: https://www.kaggle.com/datasets/arshi...