Multilingual Programming and Project Structure for Collaboration

Explore multilingual programming and project structures that enable seamless collaboration in this insightful podcast episode featuring Rodolfo Núñez. Dive into the benefits of mixing programming languages within a single project, learn about effective project templates, and understand why choosing the right language for specific problem-solving is crucial. Gain valuable insights on topics such as proper coding practices for data scientists, the importance of team collaboration, and the advantages of using tools like cookie cutter projects and Markdown. Discover strategies for improving reproducibility, managing data flows, and implementing in-house cataloging solutions. The discussion also covers MLOps security, the elbow methodology, and cross-sampling techniques, providing a comprehensive overview of modern data science and machine learning engineering practices.

[] Rodo's preferred coffee
[] Project structure
[] Introduction to Rodolfo Núñez
[] Takeaways
[] Check out our Meetups, podcasts, newsletters, TikTok, and blog posts!
[] Why data scientists should know how to code and code properly
[] Becoming a team player
[] Cookie cutter project
[] Markdown and Quarter over Jupyter notebooks
[] Data scientists' templates
[] Significance of scripts
[] Monolith to Microservices
[] Reproducibility
[] Entire event processing scripts
[] In-House cataloging solution
[] Data flows
[] Bonus topics!
[] Elbow methodology
[] Idea behind cross sampling
[] Machine Learning and MLOps Security at Entel
[] Wrap up