Data Preprocessing in Machine Learning, Cleaning, Delete rows/columns, Handle NULL values & Outliers

Описание: This video explains, Data Preprocessing in Machine Learning.

This video answers the top questions about: 

What is Data Preprocessing?
Data cleaning steps.
Read CSV file.
Deleting rows and columns.
Deleting rows and columns with conditions.
Handling NULL values with Mean, Mode, Median.
Handling Outliers in the Dataset.

Data preprocessing is a crucial step in the machine learning pipeline.

It involves transforming raw data into a clean and usable format to improve the performance and accuracy of machine learning models.

Key steps involved in data preprocessing are cleaning, integrating, transforming, Feature Selection, Feature Extraction, and Data splitting

Chapters:
00:00 Introduction: What is Data Preprocessing in Machine Learning?
00:30 Data cleaning.
00:38 Read the CSV file.
02:00 Data cleaning steps.
02:50 Deleting data frame columns.
05:03 Deleting data frame rows.
05:27 Drop rows with the condition.
06:39 Handling NULL values.
06:58 Replacing missing values.
07:30 Handling outliers.

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