Machine Learning using Sklearn and Python - 2 : Wine Classification | Machine Learning | Python

This video is all about turning you into a wine-classifying wizard using machine learning with Python's scikit-learn library! 🍷🧠 The awesome folks behind this channel are back after a short break, and they're here to teach you how to build a model that can tell where a wine comes from just by analyzing its chemistry. Sounds fancy, right? But fear not, even beginners can grasp this with this video! In this video, you'll explore: - Importing data like a pro from a giant online library (UC Irvine Machine Learning Repository, to be exact) - Using Pandas, a super cool tool to play around with and visualize the data (think charts and graphs!) - Building a machine learning model with scikit-learn, like a mini superhero for classification tasks - Using Jupyter Notebook, an interactive coding playground to bring it all to life The video dives deep into building this model step-by-step. First up, you'll learn how to import the data, which is basically a big spreadsheet with the chemical makeup of wines from different places. Then, Pandas comes in to help you understand the data better. Next, you'll use scikit-learn to build a special kind of model called a logistic regression model. This model is like a super smart judge that can look at the wine's chemistry and say "Yep, that's a Cabernet Sauvignon from California." The speaker will explain how to train this model using the data and then how to see how well it works. Finally, you'll use Jupyter Notebook to create a visual representation of how well this model is doing. Think of it like a scorecard for your wine-classifying wizard powers! The video wraps up with a promise of more machine learning adventures to come, so be sure to subscribe if you're interested! ------------------------------------------------------------------------------------------------------------------------------------------------ Previously we Have done it for Loan Eligibility (Watch it here : https://youtu.be/k34E2eiPqbE?si=5x0uNLfMDsraHvzI) For Google Collab go: https://colab.research.google.com/ ------------------------------------------------------------------------------------------------------------------------------------------------ For Enrolling in Courses: Website: https://www.yaska.co.in/ Contact: +91 89 807 50827 ------------------------------------------------------------------------------------------------------------------------------------------------ Source Code: Get it here: https://youtu.be/P3BK9_K06bI Dataset: https://archive.ics.uci.edu/dataset/109/wine Complete Playlist : https://www.youtube.com/playlist?list=PLob02JWIF-L2YJw5z0HvCh9z2m5AzlIdW TIMESTAMPS: 0:00 Intro 0:43 Exploring the Dataset 3:56 Glimpse of the project 4:36 Starting of the project - Coding the model 30:19 Outro