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Hi , I'm Anderson Ferreira

I'm a Data Scientist!!

Welcome to my Git!

Welcome to my GitHub

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🎲 Data Scientist

🔬 Currently pursuing my PhD at the Vibroacoustic Laboratory (Unicamp), with a research focus on leveraging advanced data science and machine learning techniques to address complex engineering challenges, particularly in the domains of vibration and acoustic.

🌱 Continuously expanding my expertise in Machine Learning, with focus on:

  • Building models with Scikit-learn, TensorFlow, and PyTorch;
  • Data manipulation and analysis using Pandas, Numpy, and SciPy;
  • Feature engineering, hyperparameter tuning (GridSearch/RandomSearch);
  • Cross-validation and model evaluation;
  • MLOps for deployment and monitoring of models.

💻  Machine Learning Skills:

  • Libraries/Frameworks: Scikit-learn, TensorFlow, Keras, PyTorch
  • Data Manipulation: Pandas, Numpy, SciPy
  • Model Evaluation: Cross-validation, GridSearch, RandomSearch
  • MLOps/Deployment: Docker, MLFlow, FastAPI
  • Deep Learning: Neural Networks (CNNs, RNNs)
  • NLP: NLTK, SpaCy, Hugging Face Transformers

💾 Data Engineering Skills:

  • Data Pipelines: Understanding ETL (Extract, Transform, Load) processes and automation using tools such as Apache Airflow and Bash scripting.
  • Data Warehousing: Basic knowledge of designing and populating Data Warehouses using platforms like Amazon Redshift and Google BigQuery.
  • Big Data Technologies: Experience with Apache Hadoop and Spark for handling large-scale datasets and distributed computing.
  • Databases: Working with relational databases like MySQL and PostgreSQL, as well as NoSQL databases such as MongoDB and Cassandra.
  • Cloud Computing: Basic concepts in cloud platforms like AWS and Google Cloud Platform, with a focus on deploying machine learning models and managing big data.

🛠  My Skill Set:

Programming & Tools:

  • Languages: Python, Bash, SQL, Matlab
  • Data Science: Scikit-learn, TensorFlow, Keras, PyTorch, Numpy, Pandas, Statsmodels
  • Visualization: Matplotlib, Seaborn, Plotly, Dash
  • Version Control: Git, GitHub, Docker
  • Cloud Platforms: AWS, GCP
Python Numpy Pandas Scikit-learn TensorFlow Keras PyTorch Matplotlib Seaborn Plotly Git MATLAB

⚙️  GitHub Analytics

🚀  Main Projects Repo

Data Science Projects

Exploração e modelagem de dados em Machine Learning.

Data Engineering Projects

Implementação de pipelines e arquiteturas de dados.

PhD Thesis Projects

Pesquisa aplicada em Vibroacústica e Machine Learning.

🎸 Fun fact: I’m passionate about music and play both acoustic and electric guitar!

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  1. Course_AI_Cloud_Practioner_Udemy_Frank_anderson_83 Course_AI_Cloud_Practioner_Udemy_Frank_anderson_83 Public

    Course about Cloud in Aws

  2. Course_Data_Engineering_Cloud_IBM_anderson_83 Course_Data_Engineering_Cloud_IBM_anderson_83 Public template

    This Professional Certificate is for anyone who wants to develop job-ready skills, tools, and a portfolio for an entry-level data engineer position.

  3. Course_Data_Engineering_Cloud_XP_anderson_83 Course_Data_Engineering_Cloud_XP_anderson_83 Public

    Projetos desenvolvidos em Engenharia de Dados

  4. Course_Machine_Learning_Michigan_University_anderson_83 Course_Machine_Learning_Michigan_University_anderson_83 Public

    Basic Course about Machine Learning

  5. STL_Surrogate STL_Surrogate Public

    Forked from ZaparoliCunha/STL_Surrogate

    Data and algorithms to create benchmarking analysis of ML-based surrogate models of Sound Transmission Loss (STL) analyses

    Python 1