AI in Production 2026
Published: November 19, 2025
Registration is open for the first AI in Production conference, taking place in Newcastle Upon Tyne on 4 and 5 June 2026.
Tag: Machine Learning
Jumping Rivers Webinar 4th Release
Published: November 17, 2025
Stay ahead of the curve with Jumping Rivers’ next free monthly webinar, 'Machine Learning with Python', where you’ll level up your data skills in just 55 minutes and unlock exclusive learning perks.
Elevate Your Skills with JR Training
Published: October 28, 2025
Boost your data expertise with hands-on, expert-led training from Jumping Rivers. Our experienced data scientists deliver practical courses in R, Python, Git, AI, and more, designed to help you apply new skills immediately. With flexible online and in-person options, comprehensive materials, and tailored in-house programmes, Jumping Rivers empowers individuals and teams to thrive in today’s data-driven world.
Jumping Rivers Webinar 3rd Release
Published: October 13, 2025
Join our free Jumping Rivers webinar, “Understanding Posit: Ecosystem and Use Cases,” to discover how Posit tools like Connect, Workbench, and Package Manager can power scalable, collaborative data workflows.
Jumping Rivers Webinar 2nd Release
Published: September 15, 2025
Our free monthly webinar series is back, and the first session on 21 August – “Reports that Write Themselves: Automated Reporting with Quarto” was a fantastic success! It was wonderful to see the Jumping Rivers community grow, with so many data professionals joining, engaging, and sharing ideas.
Inside Jumping Rivers
Published: September 9, 2025
At Jumping Rivers, we streamline data workflows with engineering, automation, and analytics. We handle the tasks you can’t, optimise the ones you didn’t know could be improved, and work alongside your team to make operations easier, smarter, and faster.
Time Series Forecasting in Python
Published: August 28, 2025
We introduce the ARIMA framework for time series forecasting and demonstrate the process using a real world example with Python. Along the way we explore the time series analysis functions provided by the statsmodels library and cover best practices for selecting the ARIMA model parameters.
AI In Music Production
Published: August 14, 2025
For quite some time, AI had kept it's grubby little hands out of the music production world. Now, a good percentage of the plugins (a plugin is a piece of software you can "plug in" to an audio track to add effects or generate audio) I see are advertised as "using AI". From reverb removers (yes, that's right, you can now remove the reverb from an audio recording), to EQ analysers. Today we'll focus on stem separation.
How We Do Training at Jumping Rivers: Seamless, Expert-Led, and Tailored to You
Published: August 12, 2025
When it comes to data science training, one size doesn’t fit all. At Jumping Rivers, we’ve built our reputation around delivering customised, expert-led training that actually fits your team’s goals, tools, and workflows - whether you're in healthcare, government, finance, or beyond.
Jumping Rivers Webinar Launch
Published: July 8, 2025
Are you ready to expand your knowledge in R, Python, Shiny, and Posit while becoming a more valuable asset to your team? Jumping Rivers is here to help you do just that with our free monthly webinar series designed for data professionals at all levels.
Why JR’s Training is Different
Published: June 9, 2025
At Jumping Rivers, we believe training should be more than just a tick-box exercise. It should be transformative. Whether you’re learning R, Python, SQL, Git or Posit for the first time or diving into advanced topics like machine learning and Quarto, our courses are built to help you actually use what you learn — not just watch someone code.
Vetiver: MLOps for Python
Published: February 27, 2025
Part 4 of our series of blogs on vetiver for MLOps. Having previously explained how to set up an MLOps workflow in R, we now turn to Python. This blog will introduce the vetiver package for Python and outline the key MLOps steps including model versioning, deployment and monitoring.
Training Lineup for 2025: January-June
Published: November 7, 2024
All of our public training courses for the first half of 2025 are now available to book! Head over to our public training webpage to book in and start building your programming skills in the new year! In this blog, we list all of our upcoming courses with a description, bookable dates, course level and a link to find out more.
Vetiver: Monitoring Models in Production
Published: October 31, 2024
Part 3 in our series of blogs on vetiver for MLOps. Having previously introduced the modelling and deployment steps of the MLOps workflow, we now consider the maintenance of a model in production. The monitoring process involves adding a date column to our data, scoring our model at regular time intervals, and checking for signs of model drift over time as the data evolves.
Vetiver: Model Deployment
Published: June 20, 2024
Part 2 of our series of blogs on vetiver for MLOps. In this post, we demonstrate how to deploy a machine learning model to production using Docker, Posit Connect, and SageMaker. Docker allows developers to bundle application code with necessary dependencies, simplifying deployment. We outline the process of creating a Dockerfile with the {vetiver} package and running the model locally. Additionally, we show how to publish the model to Posit Connect and SageMaker for broader accessibility.
Vetiver: First steps in MLOps
Published: June 13, 2024
Part 1 of our series of blogs on vetiver for MLOps. This post introduces MLOps and its integration into the traditional data science workflow, focusing on continuous model deployment and maintenance. It demonstrates automating data importation, creating a model with {tidymodels}, and using {vetiver} to store and deploy the model. The process includes creating an API with {plumber} and deploying it locally. Finally, it verifies the API functionality, setting the stage for future production deployments. description: Part 1 of our series of blogs on vetiver for MLOps. This post introduces MLOps and its integration into the traditional data science workflow, focusing on continuous model deployment and maintenance. It demonstrates automating data importation, creating a model with {tidymodels}, and using {vetiver} to store and deploy the model. The process includes creating an API with {plumber} and deploying it locally. Finally, it verifies the API functionality, setting the stage for future production deployments.
Training Lineup for 2024: January-June
Published: November 28, 2023
All of our public training courses for the first half of 2024 are now available to book! Head over to the public courses page on our website to book in and start building your programming skills in the new year! In this blog post, we provide a list of all of our upcoming courses with a description, upcoming dates, course level and a link to the page to find out more!
An introduction to H2O
Published: June 9, 2022
H2O.ai is a company which develops products for easy, scalable, machine learning and artificial intelligence. This post will talk through who H2O.ai are and what software they provide for your machine learning needs.
The (Delayed) 2019
Published: October 13, 2020
Don’t we all miss 2019 (blame Covid for the long delay in this post). The days of going to work and seeing your work colleagues face to face - and for some of you, attending one of our on-site training courses! 2019 was a great year for us.
