Tomás works at FC Barcelona’s Venue Business department which is responsible for selling match day and season tickets to football matches at Spotify Camp Nou.
The goal is to optimize match day revenue and fan experience, maintaining a baseline attendance. In this article Tomás shares:
It's in this article that you'll learn how similar the work on ML models is to the work on SpaceX rocket launches. Of course, this is just a pretext for a more important topic: how to enable monitoring for launched ML Models, and for this purpose we will use Vertex AI.
Vertex AI Model Monitoring can help to detect:
The Uber platform architecture uses Kafka, Flink and Pinot. The Kafka events generated by backend services, are aggregated by Flink.
Uber noticed a statistically significant boost across all key metrics since it started providing the information on performances to Freight drivers: -0.4% of late cancellations, +0.6% of on-time pick-ups, +1% of on-time drop-off and +1% of auto tracking performances.
In today’s blog, Piotr Chaberski considers the topic of the Machine Learning prototype.
After reading you will realize that it does not have to resemble a mix of spaghetti code.
You can find out how GetInData created a complete blueprint, which gives you a clear example of how to:
As of 2022 it’s estimated that less than 20% of machine learning models are brought into production. Why do so few companies bring ML models to production, and even fewer do so reliably and efficiently? Why do you need data science product teams to do MLOps?
Also, what are the requirements?
Nice lessons learned about Apache Airflow from Coinbase.
How Coinbase has revamped Apache Airflow-based the orchestration platform to ensure operational efficiency and development velocity. Experience gained in migrating pipelines and onboarding users to the revamped platform via crowdsourcing.
Many people think you need CPU limits on Kubernetes but this isn't true. In most cases, Kubernetes CPU limits do more harm than help.
Natan explains why CPU limits are harmful with three analogies between CPU starved pods and thirsty explorers lost in a desert. In this article, CPU will be water and CPU starvation will be… death.
At last, native integration with GCP. This is quite handy to manage code pipelines in SQL in BigQuery. It could be a useful addition, especially for Data Engineers and Data Analysts who only work with BigQuery.
A quick categorization of all the mentioned tools in this article:
It's great that they are moving forward with this - the combination of Snowpark + Kedro (an open-source Python framework for creating reproducible, maintainable, and modular data science code) will really be a powerful tool for MLOps, both from the perspective of ease of data processing and model training.
OK, fine, we may have missed it a bit, but it's still pretty fresh news.
Datahub got column-level lineage!
Arunabh Singh works as a director of data science at Willa - FinTech that helps professional freelancers, influencers, and social media content creators get paid immediately by brands for their freelance work and paid collaborations.
Topics of podcast:
A very interesting podcast episode with Kevin Goldsmith (CTO at Anaconda, Inc.) about the technical and social challenges that data science is facing, plus the impact that open-source software has on this industry. Recorded a year ago, but it's still worth listening to.
The relationship between data-centric AI and knowledge-first AI.
During this meeting Rafal Stryjek, Data Superhero, will demo Snowflake's streaming API, and how to use it to write data directly to Snowflake. There will be dedicated time to Q&A and networking.
A chance to speak in front of an audience of Big Data professionals.
More than 500 professionals will attend the conference to hear dozens of technical presentations. One of them could be yours ;)
The Snowflake Summit is still a while away, but now it's time for a call to arms. If you want to take part in Vegas: a story of migration, transformation or innovation, you can submit your presentation.