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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
Data Valuation – What is Your Data Worth and How do You Value it?
Editor’s Note: Come to  ODSC Europe 2019 for the talk “Data Valuation — Valuing the World’s Greatest Asset.“ Some people talk about data as the new oil, but this is too simplistic. Oil is a commodity–to be bought and sold. Data is an asset, an asset that grows in value... Read more
Deep Learning for Third-Party Risk Identification and Evaluation
Editor’s Note: Learn more about the technical details of this article at the talk “Deep Learning for Third-Party Risk Identification and Evaluation at Dow Jones” at ODSC Europe 2019 For more than 17 years, Dow Jones has supplied risk and compliance data to banking and financial institutions, corporations and... Read more
Do Android Composers Dream of Electric Keyboards?
Editor’s Note: If you’re interested in the idea of AI with a dream of electric keyboards, see Joseph’s talk “The Soul of a New AI” at ODSC Europe 2019. My journey in AI begins with grammar. Raised in a mathematical home, I think I was discovering prime numbers when... Read more
Opening The Black Box—Interpretability In Deep Learning
Editor’s Note: See Joris and Matteo at their tutorial “Opening The Black Box — Interpretability in Deep Learning” at ODSC Europe 2019 this November 20th in London. Why interpretability?  In the last decade, the application of deep neural networks to long-standing problems has brought a breakthrough in performance and... Read more
Transaction Data Enrichment, an Opportunity for Financial Wellness
Editor’s Note: See Pramod’s talk “Transaction Data Enrichment and Alternative Data: An Opportunity for Business Growth and Risk Mitigation” at ODSC West 2019.  In a recent financial wellness survey of American adults, 58% of respondents said they did not have the financial freedom to enjoy life. 48% said they... Read more
Interoperable AI: High-Performance Inferencing of ML and DNN Models Using Open-Source Tools
TensorFlow? PyTorch? Keras? There are many popular frameworks to choose from when working with deep learning and machine learning models, each with its own pros and cons for practical usability in product development or research. Once you decide which to use to train your model, you need to figure... Read more
Missing Data in Supervised Machine Learning
Editor’s note: Andras is a speaker for ODSC West 2019! this October 29 to November 1! Be sure to check out his talk, “Missing data in supervised machine learning” there. Datasets are almost never complete and this can introduce various biases to your analysis. Due to these biases, your... Read more