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Mercury library Data Science Exploration and innovation Reviews and events Vision and values Ways of working
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Data Science
Conformal Prediction: An introduction to measuring uncertainty
Data Science
Embeddings in action: behind daily life
Ways of working
From business to data: boosting AI teams
Reviews and events
Top AI conferences you can’t miss in 2024
Data Science
Smoothing risk: A Machine Learning pipeline for early debt recovery (executive summary)
Data Science
Smoothing risk: A Machine Learning pipeline for early debt recovery
Data Science
Focusing on embeddings: our latest X Project
Data Science
Explainability: how do we apply it in BBVA AI Factory?
Mercury library
Bridging the gap: Demystifying black-box algorithms with Mercury-explainability
Mercury library
The Riddle of the Lancaster House: a hands-on exercise with Mercury-Reels
Data Science
Designing strategies to cope with classification problems: a Quick Study
Mercury library
Let the trees do the work: Hands-on optimal document search with Mercury-Settrie
Mercury library
Mercury-Robust: ensuring the reliability of our ML models
Exploration and innovation
Four initiatives to drive innovation at AI Factory
Mercury library
Mercury-Monitoring: analytical components for monitoring ML models
Mercury library
Money talks: How AI models help us classify our expenses and income
Vision and values
How we are: BBVA AI Factory’s DNA
Mercury library
Mercury: Scaling Data Science reusability at BBVA
Reviews and events
Top 10 papers we discovered at NeurIPS 2022
Ways of working
How to attract and keep talent in Data?
Exploration and innovation
About Program X and why we have been awarded for this initiative
Mercury library
How to tag data faster using Active Learning
Data Science
Balancing the weight of variables in a decision tree
Reviews and events
An AWS re:Invent 2021 recap
Reviews and events
Back to on-site conferences on Data Science
Data Science
Teaching machines to assist BBVA financial advisors
Data Science
Who will validate my model? How to apply peer review to Data Science projects
Reviews and events
Recommended readings: from academia to scientific dissemination
Vision and values
Three keys to working effectively on Artificial Intelligence projects
Data Science
Applying Transfer Learning to Natural Language models
Vision and values
On route to BBVA AI Factory SL
Vision and values
From BBVA Data & Analytics to BBVA AI Factory
Data Science
Detecting balance anomalies with uncertainty models
Exploration and innovation
Explaining the reliability of algorithms to humans
Vision and values
Diversity and inclusion as a policy decision
Reviews and events
A random search at NeurIPS 2019
Reviews and events
What we saw in Graph Analytics in 2019
Data Science
Text categorization and tag suggestion in a single model
Reviews and events
What we saw (and what we showed) at KDD 2019
Data Science
Agent-based default propagation: adding politics to default propagation in the economy
Exploration and innovation
Accelerating Data Science Workflows
Reviews and events
The best events for a traveling data scientist
Reviews and events
The #10yearchallenge of Data Science
Data Science
A few Recommendations for a Data Scientist who wants to get started in Recommender Systems
Reviews and events
The most important developments in Data Science of 2018
Reviews and events
The Best Online Courses for Data Scientists
Data Science
Financial Text Classification: Methods for Word Embedding
Exploration and innovation
How Data-Driven Initiatives can Save Young Lives
Data Science
Self-Service Performance Tuning for Hive
Data Science
Improving Predictions in Deep Learning by Modelling Uncertainty
Vision and values
What Will the Bank of the Future Look Like?
Vision and values
Fairness by Design in Machine Learning is Going Mainstream
Exploration and innovation
Finding a Common Vision: Design Fiction to Establish a Dialogue among Business, Data Science and Design in Finance
Reviews and events
The Best Data Science Masters (in Spain and online) to Consider this Summer
Vision and values
Lifting the Secrecy of Algorithms with Interpretability
Exploration and innovation
An International Football Story: How to Analyze a Collective Game; Individually
Vision and values
Bringing the Artificial Intelligence to its True Potential
Exploration and innovation
Eurovision 2018. Just Another Excuse to Demonstrate the Value of Data
Vision and values
Training, an Essential Perk to Retain a Data Scientist Profile
Data Science
No Problem Too Big; No Solution Too (Computationally) Small
Data Science
Adding fairness to dynamic pricing with Reinforcement Learning
Data Science
How Kitties Helped BBVA to Detect Credit Card Fraud
Data Science
Client2vec, finding a better way to understand client’s preferences
Reviews and events
How Innovation Will Become More Customer-Focused. Our Participation at ENTER 2018
Reviews and events
What we saw at Open Data Science Conference Europe 2017
Data Science
Personalizing Banking Services with Advanced Data Analytics
Data Science
It is Not About Deep Learning, But Learning How to Represent
Exploration and innovation
Rediscovering Cities through Credit Card Data (Part 2)
Exploration and innovation
Rediscovering Cities through Credit Card Data (Part 1)
Data Science
Improving Customer Experience with Forecasting Models
Data Science
Pricing Strategy Optimization Considering Customer Sensitivity
Exploration and innovation
Measuring People’s Economic Resilience to Natural Disasters
Exploration and innovation
Experience Design in the Machine Learning Era
Data Science
There is no Such Thing as a Certain Prediction
Reviews and events
Mapping Talent at Big Data Spain