Multi-Model Classification on Wine Dataset | Machine Learning Tutorial || EDA | DS || AI ||
we will explore the wine dataset and apply multi-model classification techniques to predict the type of wine based on its attributes. We will start by introducing the dataset and then dive into the details of three different classification models: Random Forest, Logistic Regression, and K-Nearest Neighbors. We will cover topics such as data preprocessing, feature engineering, model training, and evaluation. We will also compare the performance of each model and demonstrate how to select the best model for this particular dataset. Whether you are a beginner or an experienced data scientist, this video will provide you with a practical example of how to apply machine learning techniques to real-world datasets.
Source Code :- https://github.com/sangramdhurve/EDA/...
Catch Us On Social Media :-♡
follow on Github:- https://github.com/sangramdhurve
follow on linkedin:- / samthed
follow on instagram:- / sangram_dhurve
follow on website:- https://garibaservices.blogspot.com/
Thank You for Watching :-)🤗 ❤️