Learn Data Science: Data Preprocessing in Python for Machine Learning
Data Preprocessing (in Python) is the most crucial step while solving a problem using Data Science because the real-world data is far from perfect. It can not be used directly within the Machine Learning algorithms. Hence, the data needs to be made more suitable before even beginning to use it.
Data Preprocessing refers to the steps applied to make data more suitable for data mining and then further use as input to the machine learning algorithms.
This video focuses on the implementation of Data Preprocessing methods using Python.
The second part covers the following topics:
00:00 - Introduction
02:40 - Importing the libraries
03:38 - Importing the Dataset
04:05 - Handling of Missing Data
07:45 - Handling of Categorical Data
11:35 - Splitting the dataset into training and testing datasets
13:25 - Feature Scaling
15:40 - Outro
Medium Post Link: https://bit.ly/3UXGVhZ
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Learn Data Science: Data Preprocessing in Data Mining & Machine Learning | Part 1: • Learn Data Science: Data Preprocessin...
Learn Data Science: Types of Data Sets in Data Science, Data Mining & Machine Learning(Handling the missing values): • Learn Data Science: Types of Data Set...
Learn Data Science: Data Preprocessing in Data Mining & Machine Learning | Part 2: • Learn Data Science: Data Preprocessin...
Install Jupyter Notebook: https://jupyter.org/install
Install Conda Environment: https://bit.ly/2pnH4l3
Dataset: https://github.com/tarunlnmiit/machin...
Code Notebook: https://github.com/tarunlnmiit/machin...
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