This is a repo with codes covering concepts from introductory phases up to advanced use cases of Python In Machine Learning and Data Analytics, including back propagation and regression. Authored By Mark Munyi

Repo description

Each sub-repository is named by an algorithm name, and it contains a .ipynb file which illustrates and impliments algorithms/applications/visualizations, a README file, and sub-repositories of dataset/images files (if applicable).

Programming language used in this repository is Python. There is also a custom made Machine learning package importable with pip install that details the implimentation of a Perceptron and a logistic regression model.

• Supervised learning
  • Perceptron
  • Linear Regression
  • Gradient Descent
  • Logistic Regression
  • Decision Trees
  • Deep Neural Networks
    • with TensorFlow
  • k-Nearest Neigbors
• Unsupervised Learning
  • Label Propagation
• Machine Learning package
  • Perceptron
  • Logistic regression w/ SGD
  • Testing with Pytest
  • Sample usage with real DataSet