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Sequence Modelling with Deep Learning
This is a short preview post for my upcoming tutorial  “Sequence Modelling with Deep Learning” at ODSC London in November 2019. — Much of data is sequential — think speech, text, DNA, stock prices, financial transactions, and customer action histories. Our best-performing methods for modelling sequence data use deep neural networks,... Read more
Building a Natural Language Question & Answer Search Engine
Didn’t have time to read the book for the big quiz?  Why not build a system to answer the questions for you? Using the architecture pictured below we can build out a framework that can accept natural language questions as a query and answer the question using a corpus... Read more
Lots of Data, No Labels, Now What?
Editor’s Note: Interested in learning about the problem of: lots of data, no labels? See Paolo’s talk “Guiding AI to Generate the Labels we do not have with Active Learning” at ODSC West 2019. Let me tell you about a common stereotypical data story in many industries today, simplified... Read more
Why We Need Graph Analytics for Real-World Predictions
Editor’s Note: Learn more about graphs and graph analytics at the talk “Reveal Predictive Patterns with Neo4j Graph Algorithms” at ODSC West 2019 on Wednesday, October 30th. As data becomes increasingly interconnected and systems increasingly sophisticated, it’s essential to make use of the rich and evolving relationships within our... Read more
ODSC Europe 2019 Preview: Tutorial on Automated Machine Learning
This article is co-written by Joaquin Vanschoren and Pieter Gijsbers. Today’s society increasingly relies on machine learning models for complex tasks such as decision making and personalized medicine. Constructing a good machine learning model is complicated and time-intensive. Relevant data has to be collected and cleaned, features might need... Read more
Interpretable Knowledge Discovery Reinforced by Visual Methods
Editor’s Note: See Boris Kovalerchuk’s talk “Interpretable Knowledge Discovery Reinforced by Visual Methods” at ODSC West 2019. Visual reasoning and discovery have a long history. Chinese and Indians had visual proof of the Pythagorean Theorem in 600 B.C. before it was known to the Greeks. Scientists such as Bohr,... Read more
Identifying Heart Disease Risk Factors from Clinical Text
Editor’s Note: See Sudha’s talk “Identifying Heart Disease Risk Factors from Clinical Notes” at ODSC Europe 2019.  People needlessly die every single day due to preventable heart attacks. The clues are hiding right within the notes doctors and clinicians take during routine health care visits. In this presentation, we... Read more
Solving Problems in Machine Learning with scAlign
Editor’s Note: See Nelson’s tutorial on this subject of  solving problems in machine learning at his talk “Data Harmonization for Generalizable Deep Learning Models: From Learning to Hands-On Tutorial” at ODSC West 2019. One of many common problems in machine learning (ML) is to learn models that work well... Read more
Machine Learning for Continuous Integration
Editor’s Note: Andrea Frittoli and Kyra Wulffert are presenting their talk“Machine Learning for Continuous Integration” at ODSC 2019 Europe. Continuous Integration and Data As more applications move to a DevOps model with CI/CD pipelines, the testing required for this development model to work inevitably generates lots of data. This... Read more
Machine Learning Model Fairness in Practice
Editor’s Note: See Jakub’s talk about Machine Learning “Model Fairness in Practice” at ODSC West 2019 In the last few years, the interest around fairness in machine learning has been gaining a lot of momentum. Rightfully so: our models are becoming more and more prevalent in our daily lives,... Read more