Your First Machine Learning Project - Crash Course - Feature Scaling Techniques-Avoid this untraceable mistake at all costs

4.0 (5)

38 learners

What you'll learn

This course includes

5.5 hours of video
Certificate of completion
Access on mobile and TV

Summary

Keywords

machine learning feature scaling in machine learning feature scaling how to do feature scaling in machine learning data scaling and normalization in machine learning data preprocessing in machine learning normalization vs standardization machine learning feature scaling techniques feature scaling techniques in machine learning machine learning python scaling techniques in machine learning. machine learning tutorial

Full Transcript

Welcome to the nineteenth video of the series "Build your First Machine Learning Project". In this we'll talk about Feature Scaling Techniques. Feature Scaling Techniques are used to normalize the range of independent variables or features of data but there is much more to learn. Let's understand it in deep. Chapters 00:00 Intro to Feature Scaling 01:33 Feature Scaling Techniques 11:06 How to implement Feature Scaling Techniques 13:56 Apply normalization using MinMaxScaler 15:29 Standardization done manually In order to make the best out of this, please watch this series in the order in playlist: Build Your First ML Model Playlist: https://www.youtube.com/watch?v=KSsjPbowHQ0&list=PLFAYD0dt5xCymcvacfR4CLB9Pk_9L50gz Previous Lesson: Bayesians Target Encoding: https://youtu.be/UAWPbnCUXVY Earlier Lessons: 1. Build your first ML Project: https://youtu.be/KSsjPbowHQ0 2. How to Formulate ML Problem: https://youtu.be/ygayqatDEDk 3. Setup Python Environment: https://youtu.be/Yk9BFMO6QXE 4. Jupyter Notebook Tutorial: https://youtu.be/4yuo96HtTw8 5. What is ML Modeling: https://youtu.be/Bcfk4HKgC5E 6. Reduce the size of Pandas Dataframe: https://youtu.be/Xa26NB75htg 7. What is EDA: https://youtu.be/rqCZZBrfNak 8. How to impute missing Data: https://youtu.be/Qir0Qi_CD2o 9. Mice Imputation Algorithm: https://youtu.be/BjyUbk258o4 10. How to impute missing data in categorical Variables: https://youtu.be/dm7YNsN_Nwo 11. How to Detect Outliers with Z Score: https://youtu.be/Qv2vCviL4iU 12. Mahalanobis distance: https://youtu.be/YY1lz8cOgH8 13. Cook's Distance: https://youtu.be/PVJYdMjfrAA 14. Isolation Forest: https://youtu.be/kqAxfOPlr1U 15. Feature Encoding: https://youtu.be/VzN2havYquM 16. Target Encoding: https://youtu.be/hGAbsHWitwo Let me know in the comments section if you have any questions! If you enjoyed this video, be sure to throw it a like and make sure to subscribe to not miss any future videos! Thanks for watching! #mlmodeling, #python, #machinelearning, #artificialintelligence, #pandas, #datascience

Continue this lesson in the app

Install CourseHive on Android or iOS to keep learning while you move.

Related Courses

30-Day Beginner Guitar Challenge for New Players

Master the Guitar in 30 Days: Your Ultimate Beginner Challenge! Unleash your inner guitarist with step-by-step lessons designed to transform you from novice to confident player. Join Your Guitar Academy and kickstart your musical journey today!

⭐ 4.3

36 ratings

7 hours