Juan Luis Cano Rodríguez
Madrid, Comunidad de Madrid, España
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Aerospace Engineer…
Artículos de Juan Luis
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ChatGPT, la educación, y los loros
ChatGPT, la educación, y los loros
(Adaptado del original en https://escritura.social/astrojuanlu/chatgpt-la-educacion-y-los-loros) Me llega por el…
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I am stepping down as maintainer of poliastro
I am stepping down as maintainer of poliastro
Today is Volunteer Responsibility Amnesty Day, and with a heavy heart I would like to announce that I am stepping down…
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Ha llegado el momento de exigir más a los gigantes tecnológicos que dominan nuestras vidas
Ha llegado el momento de exigir más a los gigantes tecnológicos que dominan nuestras vidas
Llevo un rato frente a la pantalla tratando de buscar el momento de publicar la edición semanal del noticiero Python…
3 comentarios
Contribuciones
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How do you implement machine learning algorithms in Python and what are some of the benefits and limitations?
Python has a huge ecosystem of libraries - which means that finding the perfect one for your problem is a skill in itself. When looking for a domain-specific or application-specific library, your best bet is to search on GitHub, PyPI or your search engine of choice for existing ones. For very specific use cases, the library might be maintained by a single person or small team, and you will need to assess if it is maintained enough and compatible with your environment. For more foundational libraries, don't miss Polars for blazing fast dataframe processing, seaborn and plotnine for elegant data visualization, pandera for data validation, transformers to interact with pre-trained AI models, and Kedro to build Pythonic data pipelines.
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How do you analyze data with R, Python, and SAS?
Despite the roaring popularity of Python, excellent teams have a rich and diverse set of tools at their disposal: R has unmatched statistical algorithms and delightful visualization libraries, SQL expressivity and approachability is unparalleled, JavaScript provides endless flexibility to build interactive experiences, and Rust is becoming more and more popular for high performance data processing. Don't become attached to a specific tool or language, embrace diversity of technologies, and be open to other programming paradigms.
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How do you analyze data with R, Python, and SAS?
One key aspect when choosing a technology stack is considering its ecosystem. Each language has its unique syntax and different people will have different preferences over it - and yet, the open source libraries built on top of a language is what empowers developers to be more productive. There is an old joke that says that "Python is the second best language for everything", and this is today more visible than ever: one can perform all data science tasks, ranging from infrastructure-as-code, web serving, data engineering, all the way to exploratory data analysis, machine learning, visualisation, dashboarding, and more. Python has become the "lingua franca" of data.
Experiencia
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Educación
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Erasmus scholarship of one year.
Licencias y certificaciones
Experiencia de voluntariado
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Organizer
PyData Madrid
- actualidad 3 años 3 meses
Ciencia y tecnología
I am the lead organizer of the PyData Madrid monthly meetups.
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Founding Member
Python España
- actualidad 12 años 4 meses
Ciencia y tecnología
Founding Member of Python Spain. I compiled the list of the first board members so they could be based in diverse geographical locations around Spain.
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Member
Space Generation Advisory Council
- 3 años 5 meses
Ciencia y tecnología
I am a member of the Events workgroup inside the Space Generation Advisory Council, where I assist in the organization of the 5th European Space Generation Workshop.
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Chair
Python España
- 6 años
Ciencia y tecnología
I was the chair of the Python España non-profit. My main activity was to handle the group social networks and chat channels, organize PyConES (our yearly conference, with +400 attendees and ~20 % women speakers in its last edition), coordinate support for the local communities and meetups, and stay in touch with everybody.
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Technical Evangelist
Pybonacci
- 4 años
Educación
I co-founded the blog Pybonacci, the first Spanish-speaking blog about scientific computing with Python. I wrote +65 articles, explaining how to use all the scientific/numerical Python ecosystem (NumPy, SciPy, Astropy, IPython/Jupyter), having reached hundreds of thousands of unique visitors.
Proyectos
Reconocimientos y premios
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Fellow
Python Software Foundation
For those who have served the Python community by creating and/or maintaining various engineering/design contributions, or for those who have served the Python community by coordinating, organizing, teaching, writing, and evangelizing.
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100 mejores calificaciones en la PAU en la UCM
Universidad Complutense de Madrid
Diploma a las 100 mejores calificaciones en la Prueba de Acceso a Estudios Universitarios en la Universidad Complutense de Madrid.
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Beca de Excelencia de la CAM
Comunidad de Madrid
Beca de Excelencia de la Comunidad de Madrid.
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Premio extraordinario de Bachillerato de la CAM
Comunidad de Madrid
Premio extraordinario de Bachillerato de la Comunidad de Madrid.
Idiomas
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Español
Competencia bilingüe o nativa
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Inglés
Competencia básica profesional
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Italiano
Competencia básica limitada
Recomendaciones recibidas
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