🎯 Let's talk about technology, politics, or any other interesting topic!
Languages and Tools:
Python: This is my go-to language! I frequently use it for data analysis and manipulation, exploring a wide range of libraries and frameworks.
R: I mainly use this for detailed statistical analysis and complex data visualizations.
Jupyter Notebook: My daily companion for writing and testing Python code, excellent for data visualization and documenting analyses.
Pandas: Essential for my work with large datasets, making data manipulation and analysis more manageable.
NumPy: I always use it for mathematical operations and numerical calculations, especially with arrays and matrices.
SciPy: A valuable tool for more scientific and technical tasks, complementing NumPy.
Matplotlib: My choice for creating static, animated, and interactive graphs, making data visualization more comprehensible.
Seaborn: I use it to enhance my statistical visualizations, thanks to its integration with Matplotlib.
Scikit-learn: One of my favorite libraries for machine learning, I frequently use it for classification, regression, and other models.
TensorFlow and PyTorch: I explore these libraries for deep learning projects, each with its unique characteristics and advantages.
SQL: An essential skill in my arsenal, I frequently use it for working with databases.
Tableau and Power BI: Tools I love using to create dashboards and reports, making data visualization more interactive and accessible.
Apache Spark: I use it to process and analyze big data efficiently, especially in distributed environments.
Git and GitHub: Fundamental to my workflow, I use them for version control and collaboration in projects.
Docker: Essential for creating isolated environments, facilitating consistent testing and deployments.
PT-BR
Paulo Henrique (Paulo Leocádia)
👋 Olá! Sou Paulo Henrique, mas pode me chamar de Paulo Leocádia.
🚀 Sou Engenheiro de Dados na DataSavvy, apaixonado por tecnologia, política e diversidade.
💼 Atualmente, estou focado na área de Ciência de Dados e também atuo como Analista de Mídia Paga na internet (tráfego pago).
🚴♂️ Nas horas vagas, gosto de pedalar no parque e assistir filmes de ficção científica e distopias. Atualmente, estou acompanhando bastante a Apple TV.
Framework for orchestrating role-playing, autonomous AI agents. By fostering collaborative intelligence, CrewAI empowers agents to work together seamlessly, tackling complex tasks.
This is a test requested by Workana for an available position at SoftExpert. The position is for a Full Stack PHP Developer. I will be developing the project using a widely popular PHP framework, Laravel, and I am still studying whether to implement Vue or React on the frontend.
Projeto de Machine Learning para prever a evasão de alunos com base no engajamento acadêmico. Inclui análise de dados, preparação, seleção de modelo, treinamento e avaliação.
Python: This is my go-to language! I frequently use it for data analysis and manipulation, exploring a wide range of libraries and frameworks.
R: I mainly use this for detailed statistical analysis and complex data visualizations.
Jupyter Notebook: My daily companion for writing and testing Python code, excellent for data visualization and documenting analyses.
Pandas: Essential for my work with large datasets, making data manipulation and analysis more manageable.
NumPy: I always use it for mathematical operations and numerical calculations, especially with arrays and matrices.
SciPy: A valuable tool for more scientific and technical tasks, complementing NumPy.
Matplotlib: My choice for creating static, animated, and interactive graphs, making data visualization more comprehensible.
Seaborn: I use it to enhance my statistical visualizations, thanks to its integration with Matplotlib.
Scikit-learn: One of my favorite libraries for machine learning, I frequently use it for classification, regression, and other models.
TensorFlow and PyTorch: I explore these libraries for deep learning projects, each with its unique characteristics and advantages.
SQL: An essential skill in my arsenal, I frequently use it for working with databases.
Tableau and Power BI: Tools I love using to create dashboards and reports, making data visualization more interactive and accessible.
Apache Spark: I use it to process and analyze big data efficiently, especially in distributed environments.
Git and GitHub: Fundamental to my workflow, I use them for version control and collaboration in projects.
Docker: Essential for creating isolated environments, facilitating consistent testing and deployments.
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent