Modal LLM LLama.cpp based model deployment as part of series of Model as a Service (MaaS)

Diabetic Retinopathy (DR) is a diabetes complication that affects the eyes. It is caused by damage to the blood vessels of the light-sensitive tissue at the back of the eye (retina). DR can lead to blindness if not detected and treated early.

Aditi @ Building Production Grade LLMs - * Thank you AI community for visiting my repository - Stay tuned for awesome Dev-ops AI Learning Resources ** ** If you find the repository useful please give it a star - Thank you for visiting my repository - Happy Learning **

A data science project focused on analyzing customer reviews from Amazon's fine food products. It involves data cleaning, exploratory data analysis (EDA), sentiment analysis, and machine learning models to predict review sentiments. Built using Python, Pandas, NLP techniques, and visualization tools like Matplotlib and Seaborn.

Prediction of home price in Azerbaijan

This project involves the development of a complete ML pipeline with tracking and deployment capabilities.

Streamlit Churn Predictor: A concise and impactful repository housing a Streamlit-based churn prediction application. Utilizes logistic regression to analyze customer data, offering businesses a powerful tool for identifying and addressing potential customer churn.

This repository demonstrates how to build a robust fraud detection system that combines supervised learning techniques with anomaly detection models. It provides end-to-end implementation, from data preprocessing and model training to deploying a real-time fraud detection API using FastAPI.

The Food Delivery Time Prediction Model estimates delivery times using regression algorithms, with XGBoost as the best performer, and is deployed as a real-time application via Streamlit.

UP-Votes predictions

A machine learning project to predict customer churn for a bank using XGBoost and Random Forest models. The project includes data preprocessing, feature engineering, model training with hyperparameter tuning, and deployment using Streamlit for real-time predictions.

The project explores multiple machine learning algorithms and evaluates their performance using various metrics, such as accuracy and confusion matrices. The models tested include Logistic Regression, K-Nearest Neighbors (KNN), Naive Bayes, and Support Vector Machine (SVM). In addition, regularization techniques (L1, L2) are used to avoid overfit.

The objective of this project is to develop a machine learning model and deploy it as a user-friendly web application that predicts the resale prices of flats in Singapore.

This repository build to showcase a project on customer personality analysis. In this I have classified the customer into two clusters.

This repository contains files from a client project aimed at developing a Streamlit app for predicting sentiment in Spotify reviews in Indonesian and English.

ML Model- Laptop Price Predictor --- https://huggingface.co/spaces/Harsh2527/LaptopPricePredictoModel

A comprehensive case study on implementing predictive modeling in insurance

Liver Disease Prediction Using ML Models. This is a Machine Learning project predicting Liver Disease i also provide model deployment , Pramod kusmude