Machine Learning Codes in Data Science

Here is a collection of machine learning codes that are useful for data science practitioners. These codes can be used for various purposes such as data preprocessing, model training, and evaluation.

Data Preprocessing

• Loading Data:

  • load_data.csv - A sample CSV file loader.
  • 

    loading_data

• Feature Scaling:

  • feature_scaling.py - Python script for scaling features.
  • 

    feature_scaling

Model Training

• Supervised Learning:

  • linear_regression.py - Linear Regression implementation.
  • 

    linear_regression
  • decision_tree.py - Decision Tree classifier.
  • 

    decision_tree

• Unsupervised Learning:

  • k_means.py - K-Means clustering algorithm.
  • 

    k_means
  • principal_component_analysis.py - Principal Component Analysis (PCA) implementation.
  • 

    pca

Model Evaluation

• Performance Metrics:
  • accuracy_score.py - Python function to calculate accuracy score.
  • 

    accuracy_score
  • confusion_matrix.py - Confusion matrix generator.
  • 

    confusion_matrix

For more detailed examples and tutorials, please visit our Data Science Documentation.