Machine Learning Tutorial Python - 6: Dummy Variables & One Hot Encoding

Machine learning models work very well for dataset having only numbers. But how do we handle text information in dataset? Simple approach is to use interger or label encoding but when categorical variables are nominal, using simple label encoding can be problematic. One hot encoding is the technique that can help in this situation. In this tutorial, we will use pandas get_dummies method to create dummy variables that allows us to perform one hot encoding on given dataset. Alternatively we can use sklearn.preprocessing OneHotEncoder as well to create dummy variables. #MachineLearning #PythonMachineLearning #MachineLearningTutorial #Python #PythonTutorial #PythonTraining #MachineLearningCource #OneHotEncoding #sklearntutorials #scikitlearntutorials Code in tutorial: https://github.com/codebasics/py/blob/master/ML/5_one_hot_encoding/one_hot_encoding.ipynb Exercise csv file: https://github.com/codebasics/py/blob/master/ML/5_one_hot_encoding/Exercise/carprices.csv Exercise solution: https://github.com/codebasics/py/blob/master/ML/5_one_hot_encoding/Exercise/exercise_one_hot_encoding.ipynb Topics that are covered in this Video: 0:00 Introduction 0:47 How to handle text data in machine learning model? 1:38 Nominal vs Ordinal Variables 2:44 Theory (Explain one hot encoding using home prices in different townships) 3:39 Coding (Start) 3:51 Pandas get_dummies method 7:48 Create a model that uses dummy columns 12:45 Label Encoder 13:29 fit_transform() method 15:40 sklearn OneHotEncoder 19:59 Exercise (To predict prices of car based on car model, age, mileage) Do you want to learn technology from me? Check https://codebasics.io/?utm_source=description&utm_medium=yt&utm_campaign=description&utm_id=description for my affordable video courses. Next Video: Machine Learning Tutorial Python - 7: Training and Testing Data: https://www.youtube.com/watch?v=fwY9Qv96DJY&list=PLeo1K3hjS3uvCeTYTeyfe0-rN5r8zn9rw&index=7 Populor Playlist: Data Science Full Course: https://www.youtube.com/playlist?list=PLeo1K3hjS3us_ELKYSj_Fth2tIEkdKXvV Data Science Project: https://www.youtube.com/watch?v=rdfbcdP75KI&list=PLeo1K3hjS3uu7clOTtwsp94PcHbzqpAdg Machine learning tutorials: https://www.youtube.com/watch?v=gmvvaobm7eQ&list=PLeo1K3hjS3uvCeTYTeyfe0-rN5r8zn9rw Pandas: https://www.youtube.com/watch?v=CmorAWRsCAw&list=PLeo1K3hjS3uuASpe-1LjfG5f14Bnozjwy matplotlib: https://www.youtube.com/watch?v=qqwf4Vuj8oM&list=PLeo1K3hjS3uu4Lr8_kro2AqaO6CFYgKOl Python: https://www.youtube.com/watch?v=eykoKxsYtow&list=PLeo1K3hjS3uv5U-Lmlnucd7gqF-3ehIh0&index=1 Jupyter Notebook: https://www.youtube.com/watch?v=q_BzsPxwLOE&list=PLeo1K3hjS3uuZPwzACannnFSn9qHn8to8 To download csv and code for all tutorials: go to https://github.com/codebasics/py, click on a green button to clone or download the entire repository and then go to relevant folder to get access to that specific file. Tools and Libraries: Scikit learn tutorials Sklearn tutorials Machine learning with scikit learn tutorials Machine learning with sklearn tutorials 🌎 My Website For Video Courses: https://codebasics.io/?utm_source=description&utm_medium=yt&utm_campaign=description&utm_id=description Need help building software or data analytics and AI solutions? My company https://www.atliq.com/ can help. Click on the Contact button on that website. #️⃣ Social Media #️⃣ 🔗 Discord: https://discord.gg/r42Kbuk 📸 Dhaval's Personal Instagram: https://www.instagram.com/dhavalsays/ 📸 Codebasics Instagram: https://www.instagram.com/codebasicshub/ 🔊 Facebook: https://www.facebook.com/codebasicshub 📱 Twitter: https://twitter.com/codebasicshub 📝 Linkedin (Personal): https://www.linkedin.com/in/dhavalsays/ 📝 Linkedin (Codebasics): https://www.linkedin.com/company/codebasics/ 🔗 Patreon: https://www.patreon.com/codebasics?fan_landing=true