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Amatofrancesco99/README.md

Hi there, I am Francesco Amato

Visitors count

✉️ Email: [email protected]
🔗 LinkedIn: Francesco Amato
💻 GitHub: Amatofrancesco99

👨‍💻 Summary

I am an Advanced Data Scientist with expertise in Data Engineering, Machine Learning (ML), and Generative AI (GenAI), particularly skilled in creating cloud solutions using Google Cloud and Microsoft Azure. My focus is on designing scalable data pipelines and ML models that transform data into actionable insights, optimizing workflows, and improving efficiency. I am passionate about Generative AI and explore its potential to address complex challenges. My work spans diverse industries, where I collaborate with teams to deliver impactful, data-driven solutions.

🗣 Languages

  • Italian: Native
  • English: Proficient (IELTS B2 level)

🛠 Technical Skills

  • Programming Languages: Python, SQL, C, C++, Java, JavaScript
  • Machine Learning Frameworks: Scikit-Learn, Keras, TensorFlow, MLFlow
  • Data Analysis: Pandas, NumPy, Matplotlib
  • Cloud Platforms: Google Cloud (BigQuery, Composer, Vertex AI), Microsoft (Azure Machine Learning, Fabric)
  • Data Engineering: Airflow, Dataform, Cloud Run, Google Analytics, Google Earth Engine
  • Other Technologies: Git, Streamlit, Tableau, LangChain, Ollama, CrewAI, RAG LangGraph, Responsible AI

📚 Certifications

  • Neo4j Certified Professional
  • Google Cloud Professional Machine Learning Engineer
  • Google Cloud Professional Database Engineer
  • Google Cloud Professional Data Engineer

💡 Most Relevant Public GitHub Projects

LLaMA First Aid

Rome, Italy | 11/2024 | LLaMA Impact Hackathon 🥈

An AI-driven app that provides real-time medical emergency support. It uses a multi-agent system that adapts to the severity of the situation, with specialized agents offering context-aware responses. The architecture integrates text and voice inputs, optimizing user interaction under stress, and features an advanced dashboard for performance monitoring.

ee-satellites

Pavia, Italy | 03/2023 - 04/2024

A Python library that simplifies satellite data acquisition and analysis, supporting sources like Landsat and Sentinel. It integrates with Google Earth Engine, accelerates data processing, and enables spectral index extraction. The library allows researchers to have datasets to be used for several purposes like machine learning for advanced analysis and predictions on satellite imagery.

Fertilizers Detection via Satellites and ML

Pavia, Italy | 03/2023 - 09/2023

This project uses satellite data and machine learning to monitor fertilizer use in agriculture, ensuring environmental regulation compliance. It analyzes spectral indices to track fertilizer application across Europe and helps reduce pollution by optimizing its usage. The system supports sustainable practices and scalable applications for biodiversity and land-use planning.

🚀 GitHub Stats

Francesco's GitHub Stats

Popular repositories Loading

  1. credit-risk-analysis credit-risk-analysis Public

    The aim is to understand which are the key factors for a certain level of credit risk to occur. In addition, some ML models capable to predict the credit risk level for a company in an year - given…

    Jupyter Notebook 25 4

  2. organic-fertilizers-detection organic-fertilizers-detection Public

    Detection of organic fertilizers (manure) application on crop fields leveraging satellite data and Machine Learning.

    Jupyter Notebook 9 1

  3. KNN-OpenMPI KNN-OpenMPI Public

    An Open MPI implementation of the well known K-Nearest Neighbors (Machine Learning) classifier.

    Jupyter Notebook 8

  4. food-recommender food-recommender Public

    A web app, whose purpose is suggesting new recipes to logged users.

    PHP 6 2

  5. llama-first-aid llama-first-aid Public

    LLAMA First Aid — your virtual first aid assistant, powered by GenAI.

    Python 6 2

  6. ee-satellites ee-satellites Public template

    A (Python) library for simplifying and accellerating satellite data acquisition

    Python 4