Javier de la Rúa Martínez @Javierdlrm
🎓 Doctoral student at @dcatkth | ML Systems 🚀 Research engineer at @hopsworks 🥋 Kyokushinkai Joined August 2015-
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Curious how @hopsworks Public Key Infrastructure has evolved over the years? Read in this article how this core component has been adapted to a #Kubernetes first-class citizen. hopsworks.ai/post/hopsworks…
Join 3k+ members to the 𝗦𝗲𝗿𝘃𝗲𝗿𝗹𝗲𝘀𝘀 𝗠𝗟 𝗖𝗼𝗺𝗺𝘂𝗻𝗶𝘁𝘆 🤗 A Discord community of ML builders 👩💻👨🏽💻 focused on building 𝗿𝗲𝗮𝗹-𝘄𝗼𝗿𝗹𝗱 𝗠𝗟 𝗮𝗽𝗽𝘀 ↓↓↓ serverless-ml.carrd.co
This is the easiest way to install Hopsworks 4.x on Kubernetes (all clouds and on-premises k8s supported).
This is the easiest way to install Hopsworks 4.x on Kubernetes (all clouds and on-premises k8s supported).
Looking forward to presenting at @pydatanyc later this week!
Looking forward to presenting at @pydatanyc later this week!
At the Feature Store Summit, @Javierdlrm presented how Hopsworks supports the snowflake schema data model. ❄️ The snowflake schema data model allows you to reduce the number of serving keys that your AI application need to make a prediction. bit.ly/3UOYt2f
Throwback to PyData Berlin and @Javierdlrm's demo on how to build a personalized Bitcoin (BTC) virtual assistant in Python. Javier uses Hopsworks and LLM function calling to do so. bit.ly/4ePqUUY
The main benefit of the #Lakehouse is openness. We have Apache projects for table formats, batch/sql and streaming query engines, and catalogs. The OSI layered architecture is a huge success. Could you imagine if the transport layer required auth/access-control by a vendor?
From London to Amsterdam! 🇳🇱🌷 @Javierdlrm and @rvanbruggen represented Hopsworks at @pydataamsterdam this week, keeping participants happy by handing out Hopsworks beers and chocolates. Thank you to everyone who listened to our talk or stopped by the booth!
My friend @Javierdlrm came up with a great analogy. Lots of people end up building their own custom #AI and #ML pipelines, but they often end up like a fragile house of cards. If you want to build great production AI/ML #systems, you need @hopsworks (and, in the picture, our…
While we get ready for @Javierdlrm 's talk at @pydataamsterdam, I will just have to restrain myself and not touch either the @hopsworks chocolate or the beer. It's a tough life.
Next week we are going to be at #pydata #amsterdam with @hopsworks . Super looking forward to lots of great discussions on our booth, and of course to @Javierdlrm's talk on thursday afternoon. Hope to see you there! (amsterdam2024.pydata.org/cfp/talk/3CJ8A…)
Hopsworks im ComputerWeekly. Als ich in Koeln in den 1990er Jahren woehnte war ich Abonnent. ComputerWeekly ist immer noch da. computerweekly.com/de/feature/Hop…
Introducing The AI Lakehouse - hopsworks.ai/post/the-ai-la… #AI #LakeHouse @hopsworks
Training ML models is easy. Transforming the data these models need is the hard part... until you learn this ↓↓↓ 𝗧𝗵𝗲 𝗽𝗿𝗼𝗯𝗹𝗲𝗺 Building a real-world ML system is > 𝟭𝟬% about training and deploying ML models, and > 𝟵𝟬% about transforming the data these models…
From our SIGMOD'24 paper, an easier read on the work we have done and are doing on making #rondb the database for real-time AI applications. If you thought #redis is good enough for real-time AI, please read this and tell us if we have changed your mind. hopsworks.ai/post/rondb-a-r…
Hopsworks 4.0 introduces support for Kubernetes deployments. Get Hopsworks up and running in minutes on any Kubernetes cluster! 🛠️ bit.ly/3W7BCQm
Introducing a query engine for AI on table formats (@apachehudi , @DeltaLakeOSS ) . Benchmarks from @sigmod show @hopsworks outperforms up to 45X Databricks, AWS, GCP. A step towards making Python a 1st class client for Lakehouse data. hopsworks.ai/post/from-lake…
PSA for data engineers. The feature store is an easy-to-use Data Warehouse that enables Data Scientists to create SCD Type 1/2/4 tables and temporal queries (point-in-time correct training data, with no leakage) - using APIs in Python (with guardrails). hopsworks.ai/post/the-featu…
We released a new blog post made jointly with the team at @hopsworks! Read it to find out how Feldera and Hopsworks.ai work together to do real-time feature engineering with Feldera computing ML features and Hopsworks handling the storage layer: feldera.com/blog/hopsworks
It was a long journey for us to be the first feature store to add support for the Snowflake Schema Data Model. This means you can add more precomputed features to your online models with minimal additional latency. hopsworks.ai/post/the-journ…
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