Train and Test splitting of Dataset | Data Preprocessing | Machine learning tutorial Hindi
Splitting of the dataset in training and testing is the most important thing to do with the dataset before taking it into a machine learning model. It is also an essential step in Data Preprocessing. we will learn how to split the dataset with the help of sklearn's API train test split.
First, we will discuss why we need to split our dataset in training and testing and what is the role of training and testing data in evaluating the performance of the machine learning model and then we will learn how to split our dataset in scikit-learn with train test split api.
Link for Data Preprocessing Course Resources :
https://drive.google.com/drive/folder...
About the Data Preprocessing Course :
We will cover all the topics which are necessary to perform on dirty data to make it clean and ready to use for the Machine learning model. The whole course is divided into six chapters and each chapter is explained through Pandas and Scikit-learn both So that your fundaments become stronger and it will definitely help you clean any kind of dirty real-world dataset. For learning purposes, we have also used a raw real-world Car dataset and we will apply our data preprocessing steps to real-world data so you get to know how to deal with the real-world dataset.
In this course,, we will start with Importing Dataset and How to get basic insights from it. then we will learn how to deal with missing values in a dataset followed by Data Formatting and Data Binning, How to Deal with categorical values, Splitting of Dataset and Feature Scaling, and Data Normalization.
About Bit ML :
Bit Ml is a youtube channel on which we upload tutorials regarding Machine Learning in python in the Hindi language so that students get detailed explanations about every topic of machine learning. Our mission is to explain complex topics of machine learning in such an easy manner that students can understand the concepts easily.
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