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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: • Build Your FIRST Machine Learning Project ... Previous Lesson: Bayesians Target Encoding: • Bayesian Target Encoding to boost model ac... Earlier Lessons: 1. Build your first ML Project: • Build Your FIRST Machine Learning Project ... 2. How to Formulate ML Problem: • Build Your First ML Project part 2: How t... 3. Setup Python Environment: • Setup Python Environment using ANACONDA 4. Jupyter Notebook Tutorial: • Jupyter Notebook Tutorial - How to Install... 5. What is ML Modeling: • What is ML Modeling? (Problem statement an... 6. Reduce the size of Pandas Dataframe: • Reduce the memory size of Pandas Dataframe... 7. What is EDA: • Exploratory Data Analysis (EDA) - Use thes... 8. How to impute missing Data: • How to handle missing data for machine lea... 9. Mice Imputation Algorithm: • Multiple Imputation by Chained Equations (... 10. How to impute missing data in categorical Variables: • How to impute missing data in categorical ... 11. How to Detect Outliers with Z Score: • How to Detect Outliers with Z Score | Clea... 12. Mahalanobis distance: • Why mahalanobis distance is incredibly pow... 13. Cook's Distance: • Understanding Cooks Distance to detect inf... 14. Isolation Forest: • Isolation Forest: A Tree based approach fo... 15. Feature Encoding: • Feature Encoding in ML: Beyond the Basics 16. Target Encoding: • Understanding Target Encoding for Categori... 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