In the previous post you got an overview of interpretability, and the different explainers available in the Interpret-Text tool. In this post, you will get an understanding of how to use one of the explainers: Classical Text Explainer. The Classical Text Explainer is an interpretability technique used... Read more
Accelerate your NLP pipelines using Hugging Face Transformers and ONNX Runtime
This post was written by Morgan Funtowicz from Hugging Face and Tianlei Wu from Microsoft Transformer models have taken the world of natural language processing (NLP) by storm. They went from beating all the research benchmarks to getting adopted for production by a growing number of companies in a record... Read more
Responsible AI: Interpret-Text
Artificial intelligence (AI) systems have a growing impact on people’s lives on an every-day-level, thus it is fundamental to protect people, understand models, and control ai systems. While machine learning (ML) services are constantly developing, Microsoft emphasizes the ethical principles that put people first, meaning that employees are... Read more
WhiteNoise is the newly available Differential Privacy System by OpenDP.  The intent of Differential Privacy is to preserve the security of personally identifiable information & prevent against database reconstruction attacks.  The methods provided by the WhiteNoise system are part of a toolkit that enables researchers to... Read more
How to Assess AI Systems’ Fairness and Mitigate Any Observed Unfairness Issues
This article discusses how we can assess AI systems’ fairness. As we are leveraging data for making significant decisions that affect individual lives in domains such as health care, justice, finance, education, marketing, and employment, it is important to ensure the safe, ethical, and responsible use... Read more
Tutorial: Accelerate and Productionize ML Model Inferencing Using Open-Source Tools
You’ve finally got that perfect trained model for your data set. Now what? To run and deploy it to production, there’s a host of issues that lie ahead. Performance latency, environments, framework compatibility, security, deployment targets…there are lots to consider! This tutorial will show you how... Read more
Training and Operationalizing Interpretable Machine Learning Models
AI offers companies the unique opportunity to transform their operations: from AI applications able to predict and schedule equipment’s maintenance, to intelligent R&D applications able to estimate the success of future drugs. However, in order to be able to leverage this opportunity, companies have to learn... Read more
How to Use Excel in Data Science for 2020
Wait, don’t leave! Excel has a terrible reputation in data science, and there is about 20 years’ worth of literature cautioning against the use of Excel in data science. There are better, faster, more agile programs that spit fancier representations and offer cooler capabilities. And here’s... Read more