Data Science Mastery: Journey into Machine Learning
Last Updated on January 13, 2025
What you’ll learn
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Gain proficiency in using Python libraries commonly used in data science and machine learning, such as NumPy, Pandas, and Matplotlib.
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Learn how to clean and preprocess datasets, including handling missing data, outliers, and feature scaling.
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Acquire knowledge of exploratory data analysis techniques to extract insights and patterns from data.
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Master the fundamentals of statistical analysis and apply statistical methods to interpret and draw conclusions from data.
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Understand the principles of machine learning and its various algorithms, such as regression, classification, and clustering.
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Learn how to select appropriate machine learning models and techniques for different types of problems and datasets.
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Develop skills in feature engineering and selection to enhance the performance of machine learning models.
