Join Machine Learning Week Europe (#MLWeek) to hear top practitioners describe the design, deployment and business impact of their #machinelearning projects.
Don’t miss your opportunity to join Europe’s most practical machine learning event—at the best possible rate!
Until 25 April, you can still get your ticket at a special discounted price. After that, prices go up.
In this talk, Simon presents a service architecture that promotes seamless collaboration between data science and operations teams.
https://t.co/jhWpWWTYqd
#mlweek#machinelearning
Muhammad Saad Uddin will outline their approach to integrating tech stacks and chatbot design, highlighting real-world industrial benefits.
https://t.co/ZI2VbqKWGQ
#mlweek#machinelearning
Miha addresses the engineering challenges of building interactive active learning systems on a practical example of large-scale video analysis.
https://t.co/zlTapREatS
#mlweek#machinelearning
Dr. Michele Dallachiesa and Andreas Leed discuss Hong Kong's challenges in managing 500+ capital projects using ML models to prevent delays and budget overruns, presenting solutions and guidelines.
https://t.co/5SFilQOzI1
#mlweek#machinelearning
In this talk Maximilian presents xLSTM, a novel architecture for LLMs that scales only linear in context length while still outperforming Transformers on language modeling.
https://t.co/PJazXWJxoz
#mlweek#machinelearning
Miha addresses the engineering challenges of building interactive active learning systems on a practical example of large-scale video analysis.
https://t.co/4CEipJKTAU
#mlweek#datascience#machinelearning
Hansel will explain how DaVita used a simpler, interpretable model to reduce hospitalizations in dialysis centers. He’ll discuss balancing model performance with clinical interpretability to gain physician buy-in.
https://t.co/3VDlSFiiEC
#mlweek#HealthcareAI
Ramón will showcase a smart assistant by Campana & Schott and Charité, designed to help healthcare professionals by suggesting treatments from guidelines and patient histories, streamlining complex decisions.
https://t.co/m6HVWO2cSH
#mlweek#HealthcareInnovation
Andre demonstrates how data-driven modeling and machine learning improve pharmaceutical manufacturing by enabling real-time testing, optimizing lead times, and predicting product quality.
https://t.co/6mORB22AZz
#mlweek#Healthcare#DataDrivenModelling
Steffen will showcase how Roche uses AI to classify visible particles in drug products, improve image data processing, and design a user-friendly application that aids data collection for continuous model improvement.
https://t.co/WSxf8Q0ebn
#mlweek#Healthcare#AIApplications
Paolo Ferriani demonstrates how Gothaer used #LLMs to efficiently extract key data from unstructured medical records, emails, and insurance forms, streamlining life insurance risk assessment.
https://t.co/u6UIcV2Ucl
#mlweek#machinelearning
Hungjen Wang would like to share his experience in how Franklin Templeton designed the architecture of the RAG system and which parts actually matter to its performance.
https://t.co/7LuGWKcExw
#mlweek#machinelearning
In this talk, Maximilian presents xLSTM, a novel architecture for LLMs that scales only linear in context length while still outperforming Transformers on language modeling.
https://t.co/970mwXSY0k
#mlweek#machinelearning
Jack and Julia will reveal how #datastorytelling promotes pharma data products and secures buy-in. Learn narrative shaping and marketing strategies, plus expert tips for your data/AI product.
https://t.co/O8r7PesUjo
#mlweek#data#machinelearning
Learn about advanced duplicate record detection using GenAI techniques.
Join this session by Ian to improve data quality.
https://t.co/fiAdmsYwZC
#mlweek#GenAI#NLP
Will Generative AI replace Data Engineers?
Join Gaurav, an engineering manager at Spotify, at ML Week Europe to explore this question and the future of data engineering.
https://t.co/lCSQD9LrYI
#mlweek#GenAI
Farah Ayadi will share the development of a context-aware conversational agent using #LLMs at Feedly AI, highlighting unique challenges and strategies for delivering accurate, consistent services to external users.
https://t.co/hKqMaLTDqt
#mlweek#ConversationalAI