Anime Rating Case Study using Python: Part 1 - Introduction and Exploratory Data Analysis

#datascience #machinelearning #python #regression #AnimeRating #casestudy #exploratorydataanalysis #FeatureEngineering #scikitlearn #linearregression #polynomialregression #programming #codingexamples #learning #tech #analytics #dataanalysis In this lecture, we will dive into the implementation of a real-world data science problem: predicting anime ratings. We will walk through the thinking process of a data scientist when presented with a problem statement and discuss how to approach the problem. I will provide an overview of the dataset and conduct exploratory data analysis (EDA) to gain insights and understanding of the data. I will walk through coding examples in Python and provide practical visualizations to make the content easy to understand and follow along. By the end of this lecture, you will have a solid foundation for implementing a regression problem statement and understand the critical steps involved in EDA. In the next lecture, we will focus on building regression models for the Anime Rating Case Study using Scikit-Learn's linear and polynomial regressors. github: https://github.com/AhmadDawood225/Data-Science/tree/main/Data%20Science/Module-2%20Supervised%20Learning%20Regression/17%2C18--case%20study linkedin: https://www.linkedin.com/in/ahmad-dawood-202753216 twitter: https://twitter.com/AhmadDa91826592

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