Rise of the Data Products Platform: Interview With Iker Martinez de Apellaniz, Adevinta – What was the value that Adevinta, the global market leader in online classifieds, gained from its Data product platform? What does the infrastructure of this platform look like? The interview with Iker Martinez de Apellaniz, Product Lead at Data Foundations at Adevinta, provides the answers to these and many other questions. It also emphasised the steps that organisations should ask before starting the process of building a platform or scaling it.
Email Optimization Through User Personalization – “Before delving into the machine learning aspect of email optimization, it is worthwhile to first consider what we would consider a perfect model and explore the realities of what we have to work with.”, starts its article Keenan Lyon, Data Scientist at LeoVegas Group. He is also a speaker at the upcoming NDSML Summit in November, where he will present more on this topic.
The Impact of MLOps on the Business Transformation – Since DevOps reached its limits in addressing the challenge on how to build, train, deploy, and scale AI and ML models, applications, products or projects in production and at a low cost, a new paradigm was introduced – MLOps. It is a collection of tools and principles that support the whole ML project life cycle and it makes the whole process more transparent and efficient. Where are the MLOps at the Gartner hype cycle in 2022? Read this article to find out.
More reading and inspiration:
EURACTIV reported that last month the EU lawmakers held their first political debate on the AI Act. The biometric recognition systems, fundamental rights safeguards, research and development exemption, EU database, and more were on the table as topics for discussion. In another article, EURACTIV summarized the unofficial position by the United States administration on the AI Act that was sent to some EU capitals and the European Commission.
Artificial Intelligence After Work (AIAW Podcast) Episode 076 with Johanna Bergman, Head of Strategic Initiatives at AI Sweden.
Artificial Intelligence After Work (AIAW Podcast) Episode 077 with Carl Thomé, Machine Learning Engineer at XLN Audio.
Artificial Intelligence After Work (AIAW Podcast) Episode 078 with Danffer Navarro, Head of Digitalization at Ericsson.
- Attend the first Data Science and Machine Learning Afterwork Party (AI Confession), on the 22nd of November in conjunction with the NDSML Summit. The party will take place at Nalen in Stockholm and will bring together the Data Science and ML community across the Nordics for a night of unforgettable networking experience. Save your spot here.
- Attend the tpo33 event that is happening on 21st of November in Stockholm. The topic of the event this time is “Citizen Data Science”. Among the things to gain by attending this event are learning how to: create citizen data scientist strategy, scale data science and AI across the organization, identify business challenges that can benefit from data science, establish company-wide data science operations, install a data science culture across the organization and much more. The event is designed for Data Science and Advanced Analytics leaders. Hurry up to be part of this tpo33 event since it is limited to 30 data practitioners.
- Attend the Data 2030 Summit and its MEA edition in March 2023 in Dubai. For the past six years the event has been gathering the Data Management community in one place and it is a platform to discuss ways of enabling faster Data Innovation and AI deployment across the enterprise by setting up a modern Data Management strategy and platform for the new decade. In 2023 the event goes beyond the Nordics and Asia Pacific regions and extends its reach to the MEA region. Explore more about this 2023 edition of the Data 2030 Summit.
- Attend the Data Innovation Summit 2023, the largest and most influential annual Data and AI event in the Nordics and beyond, in May 2023 in Stockholm. The topic of the 8th edition is “From Data & AI Transformation to Decentralised Data & AI Value Creation”. For anyone working with Data Science, Big Data, ML, AI, Data Management, Data Engineering, IoT and Analytics, etc. and anyone interested in the topics covered with this event, the registration is open.
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