How to Detect Outliers with Z Score | Clearly Explained
Welcome to the twelfth video of the series "Build your First Machine Learning Project". In this, we'll see how to detecting outliers with Z Score.
Notebook / Code link: https://github.com/machinelearningplu...
Z-score is a way to standardize the data to standard scale i.e. how far the data point is from the mean. The z-score can come positive or negative based on the help of mean and standard deviation values.
The data point away from the mean with some standard deviation is called a z-score.
So let's understand it.
Chapters
0:00 Intro
3:17 Normal and standard normal distribution
6:15 Treating Outliers
9:09 Different ways of treating outliers
11:06 Removing the outlier observation
11:21 Quantile based capping
11:15 Conclusion
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 Pro...
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Previous Lesson:
How to Detect Outliers with IQR and Boxplot? : • How to Detect Outliers with IQR and B...
Earlier Lessons:
1. Build your first ML Project: • Build Your FIRST Machine Learning Pro...
2. How to Formulate ML Problem: • Build Your First ML Project part 2: ...
3. Setup Python Environment: • Setup Python Environment using ANACONDA
4. Jupyter Notebook Tutorial: • Jupyter Notebook Tutorial - How to In...
5. What is ML Modeling: • What is ML Modeling? (Problem stateme...
6. Reduce the size of Pandas Dataframe: • Reduce the memory size of Pandas Data...
7. What is EDA: • Exploratory Data Analysis (EDA) - Use...
8. How to impute missing Data: • How to handle missing data for machin...
9. Mice Imputation Algorithm: • Multiple Imputation by Chained Equati...
10. How to impute missing data in categorical Variables: • How to impute missing data in categor...
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