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1. Detection-of-Various-Eye-Diseases-with-Machine-Learning-Methods-Using-Deep-Features Detection-of-Various-Eye-Diseases-with-Machine-Learning-Methods-Using-Deep-Features Public

   Detection of Various Eye Diseases with Machine Learning Methods Using Deep Features on MATLAB

   MATLAB 1 1

2. Possible-Sinkhole-Detection-with-MaxEnt-Modelling Possible-Sinkhole-Detection-with-MaxEnt-Modelling Public

   This study proposes the use of the Maximum Entropy (MaxEnt) model for sinkhole detection. The MaxEnt model was trained with a set of environmental and geological variables that are known to be asso…

3. NonLinear-Machine-Learning-Algorithms-Using NonLinear-Machine-Learning-Algorithms-Using Public

   Explore nonlinear ML algorithms on Hitters dataset: theory, setup, implementation, prediction, and evaluation. Python code provided. Enhance regression skills. MIT License. Contributions welcome.

   Jupyter Notebook

4. Data-Resign-and-Visualization Data-Resign-and-Visualization Public

   Data Resign and Visualization is the process of transforming raw data into visual insights. It includes cleaning and organizing data, and creating charts, graphs, and maps to uncover patterns and r…

   Jupyter Notebook

5. Classification-Models-Using-on-Diabet-Dataset Classification-Models-Using-on-Diabet-Dataset Public

   Explore nonlinear ML algorithms on the "diabetes" dataset: theory, setup, implementation, prediction, and evaluation. Python code provided. Enhance classification skills.

   Jupyter Notebook

6. Unsupervised-Learning-Techniques--K-Means--Hierarchical-Clustering--and-Principal-Component-Analysis Unsupervised-Learning-Techniques--K-Means--Hierarchical-Clustering--and-Principal-Component-Analysis Public

   This GitHub repo covers unsupervised learning: discovering patterns, structures, and relationships in data without supervision. It focuses on K-Means (clustering), Hierarchical Clustering (tree-lik…

   Jupyter Notebook