Learn the basics of data pre-processing in Python with this brief tutorial. Learn how to clean, transform, and prepare your raw data using essential techniques and popular libraries like Pandas and NumPy. Explore handling missing values, removing duplicates, scaling features, and more. Follow practical examples to gain a solid understanding of data quality and its impact on analysis results. Enhance your data analysis and machine learning skills by acquiring the necessary tools to confidently work with messy datasets and extract valuable insights. Perfect for beginners and experienced data scientists alike.
Workshop 4
Sacha (Sarah) Davis introduces the basics of data pre-processing in Python
COLAB NOTEBOOK:
https://colab.research.google.com/dri...
BREAST CANCER DATA SET:
https://drive.google.com/file/d/1Wkfo...
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Free lectures and workshops from AIMSS:
Intro lecture
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Outro lecture
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