ChatGPT for Data Science and Machine Learning
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This course covers an exciting journey in the application of ChatGPT in the field of Data Science and Machine Learning. Throughout this program, you will explore ChatGPT’s ability as a valuable tool in data analysis, preprocessing, and machine learning model building without needing to write a single line of code!
In the first part, we will dive into fundamental data analysis techniques. You will learn how to extract crucial statistical information from your datasets, handle missing values, and identify and treat outliers. We will explore the relationships between variables and the visual representation of categorical and numerical data. In the second part, we will delve deeper into the field of machine learning, and you will learn how to handle categorical attributes using techniques like LabelEncoder and OneHotEncoding. We will address the challenge of imbalanced datasets and discuss the importance of feature scaling. Cross-validation, parameter tuning, and feature selection are essential parts of the modeling process, and you will have the opportunity to enhance your skills in these areas.
Upon completing this course, you will be equipped with advanced skills in data science and machine learning, empowered to effectively apply ChatGPT in real-world projects. This program offers a unique opportunity to enhance your analytical skills and stand out in the field of data science and machine learning. Get ready to reach a new level in your professional career!
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15Categorical features - LabelEncoder
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16Unbalanced data
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17Categorical features - OneHotEncoding
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18Feature scaling
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19Train and test data
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20Algorithms and evaluation
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21Cross validation 1
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22Cross validation 2
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23Hyperparameter tuning
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24Final model
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25Feature selection
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26HOMEWORK - regression
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27Solution 1
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28Solution 2
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29Solution 3
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30Solution 4
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31Solution 5
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32Twitter dataset 1
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33Twitter dataset 2
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34Pre-processing texts
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35Sentiment analysis