Julia Silge
Positron: An IDE Specialized For Data Science
Dr. Julia Silge, Engineering Manager at Posit, joins @JonKrohnLearns to introduce Positron, a fresh open-source IDE that’s perfect for exploratory data analysis and visualization. She also lays out her top picks for LLMs that boost coding efficiency and discusses when traditional NLP methods might be the smarter choice over LLMs. Plus, Julia highlights some must-know open-source libraries that make managing MLOps easier than ever. Tune in for insights that every data scientist, ML engineer, and developer will find useful.
Watch the full interview “817: The Positron IDE, Tidy NLP and MLOps — with Dr. Julia Silge” here: https://www.superdatascience.com/817
817: The Positron IDE, Tidy NLP and MLOps — with Dr. @JuliaSilge
#PositronIDE #Tidyverse #MLOps
Dr. Julia Silge, Engineering Manager at Posit, joins @JonKrohnLearns to introduce the brand-new Positron IDE, perfect for exploratory data analysis and visualization. She also lays out her top picks for LLMs that boost coding efficiency and discusses when traditional NLP methods might be the smarter choice over LLMs. Plus, Julia highlights some must-know open-source libraries that make managing MLOps easier than ever. Tune in for insights that every data scientist, ML engineer, and developer will find useful.
This episode is brought to you by Gurobi (https://www.gurobi.com/personas/optimization-for-data-scientists/) , the Decision Intelligence Leader, and by ODSC (https://odsc.com/california) , the Open Data Science Conference. Interested in sponsoring a SuperDataScience Podcast episode? Email natalie@superdatascience.com for sponsorship information.
In this episode you will learn: • [00:00:00] Introduction • [00:03:23] Overview of Posit and Positron IDE • [00:08:33] How the needs of a data scientist differ from those of a software developer • [00:17:56] How to contribute to the open-source Positron • [00:34:52] MLOps and Vetiver: Tools for deploying and maintaining ML models • [00:48:34] Natural Language Processing (NLP) and the Tidyverse approach • [01:22:18] The role of AI and LLMs in data science education
Additional materials: https://www.superdatascience.com/817
Julia Silge | Monitoring Model Performance | RStudio
0:00 Project introduction 1:50 Overview of the setup code chunk 3:05 Getting new data 4:05 Getting model from RStudio Connect using httr and jsonlite 6:20 Bringing in metrics 9:45 Using the pins package 10:50 Using boards on RStudio Connect 13:30 Benefits of using pins 14:00 Visualizations using ggplot and plotly 17:00 Knitting the flexdashboard 18:10 Project takeaways
You can read Julia’s blogpost, Model Monitoring with R Markdown, pins, and RStudio Connect, here: https://blog.rstudio.com/2021/04/08/model-monitoring-with-r-markdown/
Modelops playground GitHub repo: https://github.com/juliasilge/modelops-playground
pins package documentation: https://pins.rstudio.com/
flexdashboard documentation: https://rmarkdown.rstudio.com/flexdashboard/
tidymodels documentation: https://www.tidymodels.org/