README.md

Machine Learning Notes

This repository contains selected notes and code snippets for Machine Learning (supervised, unsupervised) that I have created or collected and enhanced.

Technologies Used

• Python, Jupyter Notebook
• Machine Learning, Sci-Kit Learn
  • Dataset Generation
  • Regression
  • Classification
• Matplotlib

Reference

• GitHub: https://github.com/daddyjab/ML_Notes
• Jupyter Notebooks:

  • 1-Dataset Generation and Basic Linear Regression:
    https://github.com/daddyjab/ML_Notes/blob/master/1-Dataset%20Generation%20and%20Basic%20Linear%20Regression.ipynb

  • 2-Multiple Linear Regression:
    https://github.com/daddyjab/ML_Notes/blob/master/2-Multiple%20Linear%20Regression.ipynb

  • 3-Encoding Categorical Data, Scaling, and Normalization:
    https://github.com/daddyjab/ML_Notes/blob/master/4-Linear%20Models%20for%20Regression-LinearRegression%2C%20Lasso%2C%20Ridge%2C%20ElasticNet.ipynb

  • 4-Linear Models for Regression-LinearRegression, Lasso, Ridge, ElasticNet:
    https://github.com/daddyjab/ML_Notes/blob/master/4-Linear%20Models%20for%20Regression-LinearRegression%2C%20Lasso%2C%20Ridge%2C%20ElasticNet.ipynb

  • 5-Linear Models for Classification-Logistic Regression:
    https://github.com/daddyjab/ML_Notes/blob/master/5-Linear%20Models%20for%20Classification-Logistic%20Regression.ipynb

  • 6-Decision Trees:
    https://github.com/daddyjab/ML_Notes/blob/master/6-Decision%20Trees%20and%20Logistic%20Regression%20(with%20Scaling).ipynb

  • 7-Cross Validation:
    https://github.com/daddyjab/ML_Notes/blob/master/7-Cross%20Validation.ipynb

  • 8-Hyper-Parameter Tuning:
    https://github.com/daddyjab/ML_Notes/blob/master/8-Hyper-Parameter%20Tuning.ipynb

  • 9-Neural Networks:
    https://github.com/daddyjab/ML_Notes/blob/master/9-Neural%20Networks.ipynb

  • 10-Handwriting Recognition:
    https://github.com/daddyjab/ML_Notes/blob/master/10-Handwriting%20Recognition.ipynb

Visualizations

Figure: 1-Dataset Generation and Basic Linear Regression - Jupyter Notebook

Figure: 2-Multiple Linear Regression - Jupyter Notebook

Figure: 3-Encoding Categorical Data, Scaling, and Normalization - Jupyter Notebook

Figure: 4-Linear Models for Regression-LinearRegression, Lasso, Ridge, ElasticNet - Jupyter Notebook

Figure: 5-Linear Models for Classification-Logistic Regression - Jupyter Notebook

Figure: 6-Linear Models for Classification-Decision Trees - Jupyter Notebook

Figure: 7-Cross Validation - Jupyter Notebook

Figure: 8-Hyperparameter Tuning - Jupyter Notebook

Figure: 9-Neural Networks - Jupyter Notebook

Figure: 10-Figure-Handwriting Recognition - Jupyter Notebook