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ElsonFilho/README.md

Hi, I'm Elson

Senior AI & Machine Learning Engineer

📍 Based in Switzerland | 22+ years in Data Science & ML

Currently Working On

  • Building production-ready Generative AI applications with LLMs and RAG systems
  • Exploring AI Agents and autonomous systems
  • Developing Deep Learning solutions using PyTorch, TensorFlow and Keras
  • Implementing end-to-end MLOps pipelines for scalable ML deployment

Technical Stack

AI & Machine Learning (Primary Focus)

  • GenAI/LLMs: LangChain, RAG, Fine-tuning, Prompt Engineering
  • Deep Learning: PyTorch, TensorFlow, Keras
  • Classical ML: Scikit-learn, XGBoost, Random Forests
  • Computer Vision & NLP

Engineering & Tools

  • Languages: Python, R, SQL, SAS
  • MLOps: Docker, MLflow, CI/CD
  • Cloud: AWS, Azure, GCP

Additional Expertise

  • Machine Learning with SAS: 22+ years developing ML models in enterprise environments
  • Business Intelligence: Power BI, SAS VA, data visualization, executive dashboards
  • Statistical Computing: R, Advanced Analytics

Connect With Me

LinkedIn | Email

⭐️ Check out my pinned repositories below for examples of my recent work

Pinned Loading

  1. GenAI GenAI Public

    Comprehensive Generative AI and LLMs - transformers, RAG, fine-tuning, and production applications with HuggingFace and LangChain

    Jupyter Notebook 1

  2. AI-Agents AI-Agents Public

    Multi-agent AI systems with crewAI and LangGraph - autonomous task planning, collaboration patterns, and real-world applications

    Jupyter Notebook 1

  3. Deep-Learning-Fundamentals Deep-Learning-Fundamentals Public

    Deep learning fundamentals - neural networks, CNNs, RNNs, Transformers, backpropagation, and activation functions with Keras/TensorFlow

    Jupyter Notebook 1

  4. Python-AI-Applications Python-AI-Applications Public

    Modern AI applications in Python - image captioning, audio transcription with Whisper, chatbots, and computer vision with PyTorch/Gradio.

    Jupyter Notebook 1

  5. Python-Machine-Learning-Complete-Guide Python-Machine-Learning-Complete-Guide Public

    Comprehensive machine learning fundamentals - supervised/unsupervised learning, model evaluation, and real-world projects with scikit-learn.

    Jupyter Notebook 1

  6. Python-Data-Science-Reference-Guide Python-Data-Science-Reference-Guide Public

    End-to-end data science reference - importing, wrangling, EDA, modeling, and evaluation with practical code snippets

    Jupyter Notebook 1