Mahdi Navaei
MahdiNavaei
Senior ML Engineer | GenAI: LLM Agents + RAG | FastAPI • PyTorch • Docker
Languages
Repos
30
Stars
164
Forks
24
Top Language
Jupyter Notebook
Loading contributions...
Top Repositories
The Google Scholar Scraper is a Python program that allows users to extract articles from Google Scholar based on the provided title or keyword.
Project aimed at training a deep learning model using Convolutional Neural Networks (CNN) for high-accuracy (over 99%) blood cancer detection, utilizing a large dataset of blood cell images.
Repositories
30No description provided.
The Google Scholar Scraper is a Python program that allows users to extract articles from Google Scholar based on the provided title or keyword.
Project aimed at training a deep learning model using Convolutional Neural Networks (CNN) for high-accuracy (over 99%) blood cancer detection, utilizing a large dataset of blood cell images.
Local-LLM, Evidence-first, Audit-ready Invoice Processing
AI-powered pharmaceutical supply chain management using LangGraph agents, OpenAI GPT-4, and optimization algorithms.
No description provided.
🤖 Production-grade Agentic AI Framework | Vision + LLM + Event Sourcing | Local LLMs | LangGraph | HITL Safety | Autonomous Task Execution
resume
🚀 Production-ready hybrid recommender system for e-commerce. Combines collaborative filtering & content-based ML with FastAPI backend, React
AI-powered Surge Pricing & ETA Optimization for ride-hailing platforms. Using demand forecasting and real-time ETA predictions, it optimizes fares, reduces wait times, and improves driver/passenger experience. Optimized for Tehran, it helps increase revenue and reduce pricing volatility.
Real-time dashcam collision risk prediction with BADAS-Open, FastAPI backend, and a bilingual React dashboard.
Reproducible credit-card fraud benchmark on Kaggle with Optuna tuning, PR-based thresholding, and publication-ready plots; compares ParaBoostForest, RF, and XGBoost.
No description provided.
This repository contains a deep learning project that focuses on emotion classification using Convolutional Neural Networks (CNNs). The goal of this project is to separate images into two distinct categories: "Sad" and "Happy" emotions.
No description provided.
This repository contains a Python script that retrieves historical EUR/JPY exchange rates from the Twelve Data API and applies an ARIMA (Autoregressive Integrated Moving Average) model to predict future exchange rates.
No description provided.
No description provided.
No description provided.
My effort has been to do this project with logistic regression
No description provided.
No description provided.
No description provided.
Customer Personality Analysis is a detailed analysis of a company’s ideal customers. It helps a business to better understand its customers. It makes it easier for them to modify products according to the specific needs, behaviors, and concerns of different types of customers.
No description provided.
No description provided.
Foot Size Detection using Python and OpenCV
No description provided.
No description provided.
No description provided.