CloudCV GSoC Ideas

Sales Conversion Optimization MLOps: Boost revenue with AI-powered insights. Features H2O AutoML, ZenML pipelines, Neptune.ai tracking, data validation, drift analysis, CI/CD, Streamlit app, Docker, and GitHub Actions. Includes e-mail alerts, Discord/Slack integration, and SHAP interpretability. Streamline ML workflow and enhance sales performance.

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

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.

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.

Building and deploying a convolutional neural network (CNN) for accurately classifying landmarks from images using both custom CNNs and transfer learning techniques.

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

Project 1 for Udacity Machine Learning Nanodegree

A Question Answering (QA) system built on a pre-trained BERT model to generate accurate, context-aware responses. By encoding both questions and context with BERT embeddings, the system identifies the most relevant answer spans, delivering fast and high-quality results across various domains like customer support and information retrieval.

🎲 Create dynamic interactive stories with AI, offering unique plots, characters, and visual story maps based on player choices for an immersive experience.

🤖 This repository contains various machine learning implementations and experiments, focusing on fundamental ML concepts and applications.

CM3015 Machine Learning and Neural Networks Final - University of London

R Markdown project for analyzing telecom customer churn using EDA and machine learning models.

AutoMLPrediction is a comprehensive, automated machine learning (AutoML) platform designed to simplify the process of building, training, and deploying machine learning models. The platform leverages state-of-the-art AutoML techniques to enable users, regardless of their technical expertise, to make accurate predictions from data effortlessly.

This project predicts a property's Sustainable Habitability Score using machine learning, providing insights for smarter housing decisions. Inspired by Kaggle Playground Series S3E14 and part of #MLOlympiad,

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.

Boston house prices prediction for machine learning nanodegree

Anomaly Detection Web Application using Dynamic Ensembles and SHAP Explanations

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