Machine Learning Basics | Chapter 5: Data Preprocessing for Machine Learning by Prakhar Chauhan | Learn Smarter
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Chapter 5: Data Preprocessing for Machine Learning

Data preprocessing is a crucial step in machine learning that involves cleaning and altering raw data to ensure it is suitable for algorithms. It addresses missing values, encodes categorical data into numerical formats, and scales features to enhance the accuracy of predictions. Effective preprocessing enhances model performance and leads to more reliable outcomes.

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Sections

  • 5

    Data Preprocessing For Machine Learning

    This section introduces data preprocessing, its importance in machine learning, and techniques for handling missing data, encoding categorical data, and feature scaling.

    Learning Practice

  • 5.1

    What Is Data Preprocessing?

    Data preprocessing is the crucial step of cleaning and transforming raw data before it is used in machine learning algorithms.

    Learning Practice

  • 5.2

    Importing A Dataset

    This section introduces the process of importing a dataset into a pandas DataFrame for further data preprocessing in machine learning.

    Learning Practice

  • 5.3

    Handling Missing Data

    This section focuses on methods for managing missing data in datasets, emphasizing the importance of handling NaN values effectively.

    Learning Practice

  • 5.4

    Encoding Categorical Data

    Encoding categorical data is essential for machine learning models as they primarily understand numerical inputs.

    Learning Practice

  • 5.5

    Splitting Dataset Into Training And Test Set

    This section explains the importance and method of splitting a dataset into training and test sets for evaluating machine learning models.

    Learning Practice

  • 5.6

    Feature Scaling

    Feature scaling is essential in machine learning to ensure that all features contribute equally to the model's performance by adjusting their ranges.

    Learning Practice

References

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Class Notes

Memorization

What we have learnt

  • Data preprocessing involves...
  • Handling missing data and e...
  • Feature scaling ensures tha...

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