## **Automatic** Incisive-teeth Selection And Extraction

** (Computer Vision) ** Given a training set of panoramic dental X-Rays, a program was designed and trained to locate and extract the 4 upper incisor teeth automatically.

## **Time-series** Prediction

** (Recursive Least Squares Support Vector Machines) ** For predicting future values on a Time-series, I used Least Squares Support Vector Machines as a powerful non-linear autoregressive model.

## **Feedforward Artificial Neural Network**, **complete Python** implementation using only Numpy and Scipy

** (Artificial Neural Networks) ** This is my take in programing a Feedforward Artificial Neural Network with **tanh activation functions** and **cross-entropy loss function** __WITHOUT using any ML packages__. In this implementation I also programmed:

1) L2 regularization, 2) Drop-out regularization, 3) the same network using TensorFlow.

## **Images Classification**, using Convolutional Neural Networks and ensambles of learners

** (Deep Learning) ** I built a **Conv-NN** for classifying images of dogs by breed (available here). I used a One-vs-All approach to make every learner (Conv-NN), in an **ensamble of learners**, to correctly identify one breed from the rest. The complete ensamble then sees every image and gives a probability of belonging to the class. The image is assigned to the class with highest probability.