Data Formatting and Data Binning in python pandas | Data Preprocessing | Data Minning | Hindi.
Data Formatting and Data Binning can lead your data preprocessing skills to the next level and helps you to become a better Data Scientist or Machine learning engineer. In this tutorial, we have a detailed discussion on how to correct incorrect data types in the dataset and why we see incorrect data types, and how they are related to null values in the dataset. Then I have explained Data Binning in detail which expands your understanding of Data Preprocessing. Data Binning is a very useful technique to distribute your data in certain intervals of categories. We will perform data formatting and data binning on a real-world dataset so you get familiar with how things work with a real-world dataset.
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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