Machine Learning Engineer Nanodegree

About

This repository contains projects associated with Udacity’s Machine Learning Engineer Nanodegree, that I’ve worked on. All the code can be find here https://github.com/moisesvw/udacity-machine-learning

Projects

1 - Predicting Boston Housing Pricing

Built a model to predict the value of a given house in the Boston real estate market using various statistical analysis tools. Identified the best price that a client can sell their home utilizing machine learning.

2 - Finding Donors for CharityML

In this project, I reviewed factors that affect the likelihood of charity donations being made based on real census data — developed a naive classifier to compare testing results — trained and tested several supervised machine learning models on preprocessed census data to predict the likelihood of donations — selected the best model based on accuracy, a modified F-scoring metric, and algorithm efficiency.

3 - Creating Customer Segments

Reviewed unstructured data to understand the patterns and natural categories that the data fits into. Used multiple algorithms and both empirically and theoretically compared and contrasted their results. Made predictions about the natural classes of various types in a dataset, then checked these predictions against the result of the unsupervised analysis.

4 - Object Classification

Implemented a convolutional neural network to classify images from the CIFAR-10 dataset

5 - Dog Breed Classifier

I have built an algorithm to identify canine breed given an image of a dog. If a given picture of a human, the algorithm identifies a resembling dog breed.

6 - Training a Smartcab to Drive

Applied reinforcement learning to build a simulated vehicle navigation agent, This project involved modeling a complex control problem in terms of limited available inputs and designing a scheme to automatically acquire an optimal driving strategy based on rewards and penalties.