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Silvestre17/README.md

OlΓ‘! πŸ‘‹ I'm AndrΓ© Silvestre

From Portugal πŸ‡΅πŸ‡Ή, passionate about turning data into intelligent systems. Currently engineering ML pipelines and AI Agents at JTA - The Data Scientists and teaching LLMs to navigate Lisbon for my thesis.

I consider myself introverted 🀫 but communicative πŸ’¬, and very perfectionist 🎯 (Yes, even aligning my Jupyter Notebook cells perfectly!) in everything I do. Think of me as a meticulous algorithm – I'm always optimizing!

I always try my best. I love technology πŸ–₯️, news πŸ—žοΈ, and knowledge 🧠, which is why I took the Data Science course. At the moment, I'm interested in areas such as πŸ€– Machine and Deep Learning and AI! πŸš€

Fluent in Python, but my debugging skills are still learning the language! 🐍

About me:

  • πŸ€– Currently engineering ML & AI pipelines at JTA β€” The Data Scientists (Jan 2026 – Present)

  • πŸŽ“ Finishing my MSc in Data Science and Advanced Analytics @ NOVA IMS β€” Academic Merit Honor Roll 2024/2025 (GPA: 19.2/20)

  • πŸ™οΈ Master's Thesis: LISBOA β€” LLM-powered multi-agent system that builds real-time itineraries for Lisbon using 6 specialised agents, live transport data, IPMA weather & multilingual RAG

  • πŸ‘¨β€πŸ’» All of my projects are available at GitHub Repository

  • ⚑ Fun fact: I love cooking 🍳 (still waiting for the day when AI can perfectly season my dishes) and learning more about everything πŸ”, because "The important thing is not to stop questioning" πŸ§ πŸ’‘ (Einstein).

  • πŸ“« How to reach me LinkedIn andrefgsilvestre


🧠 Languages:

Python SQL R PySpark Markdown LaTeX

πŸ“‚ Databases:

MySQL MongoDB Neo4j ChromaDB

🌐 Web Development:

Streamlit HTML5 CSS Django

πŸ“Š Data Science & Machine Learning:

NumPy Pandas Polars Scikit-Learn XGBoost/LightGBM/CatBoost
Matplotlib Seaborn Plotly
SciPy igraph NetworkX PuLP
BeautifulSoup Selenium

πŸ€– Agentic AI & LLMs:

TensorFlow Keras PyTorch Hugging Face
LangChain LangGraph Pydantic AI RAG

πŸ› οΈ Tools & Cloud:

Linux Bash Git GitHub Docker Azure Databricks AWS
PyCharm Jupyter VS Code

πŸ€– AI Assistants & Productivity:

ChatGPT Grok Google AI Studio
GitHub Copilot Hugging Face

πŸ“ˆ Data Visualization:

Tableau Power BI RStudio

GitHub Stats:

Silvestre17


WakaTime Stats:

Silvestre17

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  1. ChatMeter_FinalProject.inDataScience ChatMeter_FinalProject.inDataScience Public

    πŸ’¬ Capstone project for the Data Science bachelor's at ISCTE. "ChatMeter" is an AI solution analyzing social media sentiment and topics for Portuguese telecom operators using Transformers.

    Jupyter Notebook 1

  2. DL_RareSpecies_ImageClassification_MasterProject DL_RareSpecies_ImageClassification_MasterProject Public

    🌿 Deep Learning project classifying rare species from images using the BioCLIP dataset. Features transfer learning (ConvNeXtBase), innovative data cleaning with CLIP (zero-shot), and imbalance hand…

    Jupyter Notebook 3 1

  3. CIFO_MusicFestivalLineup_GeneticAlgorithm_MasterProject CIFO_MusicFestivalLineup_GeneticAlgorithm_MasterProject Public

    🎢 Using a Genetic Algorithm (GA) to solve the multi-objective music festival lineup problem: maximizing popularity & diversity while minimizing fan conflicts. Developed for the CIFO course at NOVA …

    Jupyter Notebook 1 1

  4. NEL_ChickenProteinPrediction_MasterProject NEL_ChickenProteinPrediction_MasterProject Public

    πŸ” Master's project comparing 6 Neural & Evolutionary Learning models (GP, NEAT, NNs) to predict protein in chicken carcasses using a 10x10 Nested CV. Developed for the NEL course at NOVA IMS.

    Jupyter Notebook 1 1

  5. DM_FoodDeliveryClustering_MasterProject DM_FoodDeliveryClustering_MasterProject Public

    πŸ• Data Mining project for "ABCDEats Inc." using clustering (K-Means, SOM) to segment customers based on purchasing behavior. Includes an interactive Streamlit dashboard for exploration. Developed f…

    Jupyter Notebook 1 1

  6. ML_PredictingWorkersCompensationClaimSeverity_MasterProject ML_PredictingWorkersCompensationClaimSeverity_MasterProject Public

    πŸ€– Machine Learning project to predict the severity of workers' compensation claims using CatBoost & Random Forest. Deployed as an interactive Streamlit app with LIME for interpretability. Developed…

    Jupyter Notebook 2 3