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Working from home
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JoAmps/README.md

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An AI/Machine Learning Engineer and backend developer with over five years of experience delivering AI/ML solutions and building robust backend systems across diverse industries. Currently, I am building SaaS and agentic applications powered by generative AI, focusing on large-language models (LLMs) and LMMs (Large Multimodal Models).

My expertise includes:

• End-to-end Solution Design: Architecting AI/ML solutions from the ground up, aligning technical frameworks with business objectives for scalable, impactful outcomes.

• Backend Development: Designing and implementing scalable, secure, and high-performance backend systems and APIs using python to support AI-driven applications and data pipelines.

• Model Development and Deployment: Training, fine-tuning, and deploying LLMs and custom AI models using advanced frameworks to meet specific business needs.

• Cloud and MLOps Practices: Optimizing AI/ML models on GCP and AWS with a focus on scalability, reliability, and cost-efficiency, while implementing containerization, CI/CD, monitoring, and logging for production-grade systems.

• Generative AI Expertise: Leveraging cutting-edge LLM and LMM frameworks to create transformative applications and products

📭 You can reach out to me on Hyacinth Ampadu | LinkedIn and also on my email here ampaduh@gmail.com

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  1. KidFriendlySocial-KFS- KidFriendlySocial-KFS- Public

    A safe social media webapp using NLP models(BERT and GPT3) for bad language detection and content recommendations, deployed using docker and Kubernetes on digital ocean

    Python

  2. Lead_conversion_prediction_for_a_mobile_app_company Lead_conversion_prediction_for_a_mobile_app_company Public

    Predicting if a lead would convert on an app, deployed using fastapi, with streamlit as frontend via CI/CD using GitHub Actions, and containerised using Docker

    Jupyter Notebook 2

  3. bert-based-health-and-Fitness-sentiment-system bert-based-health-and-Fitness-sentiment-system Public

    Train and build a sentiment model using pytorch for fitness apps using Bert, dockerized and container deployed to the cloud(AWS)

    Jupyter Notebook 2

  4. Classical-Machine-Learning-Folder Classical-Machine-Learning-Folder Public

    Building complex Machine learning models to make predictions on data

    Jupyter Notebook 2

  5. JoAmps-Udacity-Machine-learning-Devops-Engineer-Nanodegree-MLOPS- JoAmps-Udacity-Machine-learning-Devops-Engineer-Nanodegree-MLOPS- Public

    My projects in the Udacity MLOPS nano degree course

    Jupyter Notebook 4 1

  6. Churn-prediction-in-a-vehicle-insurance-company-in-Ghana Churn-prediction-in-a-vehicle-insurance-company-in-Ghana Public

    Predicting customer churn in a vehicle insurance company in Ghana, deployed on Heroku, via CI/CD using GitHub Actions and set up monitoring to detect model and concept drifts

    Jupyter Notebook 1