Carlos Vecina is a data scientist with experience using ML and AI to bring value to business in CRM, Marketing and energy markets environments.
Interests
- Artificial Intelligence
- Time Series Forecasting
- Deep Learning
- Uncertainity
- Econometrics
Education
Pre PhD Research in Artificial Intelligence. Computer Vision and pose estimation., 2019
UNED
MSc Data Science for Finance, 2017
CUNEF
Latest
- Data Engineering Bootcamp 2024 (Week 2) Mage & GCP ETL orchestation
- Data Engineering Bootcamp 2024 (Week 1) Docker & Terraform
- Plot your GIS data with GeoPandas and Plotnine. A single glance insightful visualization
- Plot_ss in R. Smoothing splines and polynomial regression plots
- Python protocols. When to use them in your projects to abstract and decoupling
- Boosting Python development speed with Ruff: An all-in-one lightning fast linter
- Measure FWHM from image with Python
- Add new not nullable column while working with SQLModel and Alembic migrations.
- Shadowing your Plotnine lines in Python. Forecasting confidence interval geom_ribbon.
- Pydantic parse objects with parse_obj and parse_obj_as methods
- Unlocking the Power of GPT-4V: The Multimodal Revolution
- Polars: Filter rows and columns based on percentage of NAs / nulls
- Mastering Python Polars json manipulation. Do it in an easy and robust way!
- Sort in Python Polars. Arrange your DataFrames and Series
- How to upper strip in Python
- Fix the error: cannot import name 'MultiHostDsn' from 'pydantic.networks'
- Efficient Column Selection in Polars: Utilizing Polars Selectors for Python DataFrame Manipulation
- Polars new feature. Suggest more efficient Polars method for apply lambda functions
- Select datetime columns matching time zones with Python Polars selectors. Calculate offset with the new dst_offset.
- How to create a Streamlit datetime slider.
- New Streamlit Chat. Conversational app with st.chat_message and st.chat_input
- Pydantic discriminated unions. Some examples to simplify data structures and ensure type safety
- Ursina vector rotation. The right and easy way to deal with this 3d Python module!
- Launching The Project Tracker. Open Source project monitoring and release explainer with Streamlilt and LLMs
- Pipe function in Python Polars. Don't leave the pipe flow!
- Financial Markets & Value Invest in R (I) - Analyzing Market Cap data with fmpcloudr and ggplot
- Mock Celery task in Pytest
- Git recursive add files
- Pydantic, Enums and IntEnums. A Story of Validation
- @staticmethod in Python
- Analyzing Remote Work in European Countries
- Revisiting normality tests in Python
- Customize your Label and Independent transformer inside a Scikit Learn Pipeline
- Playing with a new R package; Welcome ggcharts!
- Speed up your R scripts. A cool optimized way to load, write and store big data frames with FST package!
- Drop columns based on NAs percentage in R
- 10 Tips to ace your Kaggle, Datathon or any data competition!
- Pathfinding Algorithms Visualizer using R! (I) Setting up the interactive grid
- Using summarise_at(). Weighted mean Tidyverse approach
- List all the defined variables in Jupyter Notebooks
- Skills chart using Gplot2 with R
- Reordering bars in GGanimate visualization
- Shadowing your ggplot2 lines. Forecasting confidence interval in R use case.
- Data competition platforms
- Counting NAs by column in R
- Turn your GGplot to 3D animation. Awesome 2D to 3D plots in R with Rayshader