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Hi everyone, today I examined the 'Student Performance Factors' dataset, which is another dataset I accessed via Kaggle. I think that I advanced the data science process from A to Z through these parameters, as it really has a wide variety of parameters in terms of content. While testing ourselves and learning new things by cleaning data, visualizing data, detecting outliers and eventually producing estimated grades with machine learning, I also tried to go over some of its structures again. In addition, I tried to draw meaningful conclusions from the data after using many types of graphics and examining them during the data visualization phase. I hope it will be useful and helpful for you. Enjoy watching. If you want to examine and work on the dataset; https://www.kaggle.com/datasets/laing... sections: 00:00 Introduction 03:13 General Information 09:33 Filling Empty Data 12:54 Data Visualization and Analysis 01:16:19 Making Data Suitable for Machine Learning 01:28:51 Machine Learning