CloudCV GSoC Ideas

Udacity Machine Learning Nano degree Program. Project Predicting House prices in Boston

This project focuses on using the AWS open-source AutoML library, AutoGluon, to predict bike sharing demand using the Kaggle Bike Sharing demand dataset.

Builded 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 house utilizing machine learning.

The primary objective of this project was to build and deploy an image classification model for Scones Unlimited, a scone-delivery-focused logistic company, using AWS SageMaker.

Project 1 for Udacity Machine Learning Nanodegree

Boston house prices prediction for machine learning nanodegree

Udacity Model Evaluation Project

Exercises from 'An Introduction to Statistical Learning with Applications in R' by James et al.

Udacity project on using linear regression to predict housing prices in Boston.

This project leverages deep learning to predict Covid-19 patient mortality. The model is trained on a dataset generously provided by the Mexican government. It places a strong emphasis on crucial stages, including comprehensive data analysis and rigorous model training, with the ultimate goal of delivering a highly accurate deep learning model.

Comparing support vector classifier and neural network on the Iris dataset.

Image Classifiers are used in the field of computer vision to identify the content of an image and it is used across a broad variety of industries, from advanced technologies like autonomous vehicles and augmented reality, to eCommerce platforms, and even in diagnostic medicine.

This project aims to develop a robust classification model using test-takers' demographics and questionnaire responses from the ASD screening dataset to accurately identify individuals with Autistic Spectrum Disorder (ASD) through optimization of performance metrics.

Anomaly Detection Web Application using Dynamic Ensembles and SHAP Explanations