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