Some basic AI/ML/DL algorithms implemented from scratch for understanding purposes. Here I will be using only numpy and some basic libraries only.
- Basic Deep Neural Network using Gradient Descent for Backpropogation
- Linear Regression
- Logistic Regression
- Logistic Regression using Gradient Descent
- Linear Regression using Gradient Descent
- Decision Tree Classifier
- Decision Tree Regressor
- Support Vector Machines
- Naive Bayes
- K-Nearest Neighbors Classifier/Regressor
- K-means
- Agglomerative Hierachical Clustering
- Random Forest Classifier/Regressor
- Density based spatial clustering for application with Noise
- Gradient Boosting Classifier/Regressor
- Meanshift Clustering