For Data Scientists, It’s Always Decision Time | by TDS Editors | May, 2022

For Data Scientists, It's Always Decision Time |  by TDS Editors |  May, 2022

Data scientists help their colleagues make the best, most informed decisions possible. Their work becomes even more valuable when it empowers stakeholders to opt for counterintuitive or less-conventional choices that they wouldn’t have considered otherwise. Shouldn’t we also pay attention to the decisions data scientists themselves make, though? Every data-informed insight, after all, is the … Read more

Causal Inference with Linear Regression: Endogeneity | by Aaron Zhu | May, 2022

Causal Inference with Linear Regression: Endogeneity |  by Aaron Zhu |  May, 2022

Discussion of Exogenous variables, Exogenous variable, Omitted variable, Measurement Error, and Simultaneity Bias Image by Author In my previous article, we discussed some common issues when designing a linear regression — Omitting Important Variables and Including Irrelevant Variables. In this article, we’ll discuss Endogeneity in a linear regression model, especially in the context of Causal … Read more

20 Open-Source Single Speaker Speech Datasets | by Ng Wai Foong | May, 2022

20 Open-Source Single Speaker Speech Datasets |  by Ng Wai Foong |  May, 2022

A comprehensive open-source multi-lingual speech data Photo by Jason Rosewell on Unsplash Speech synthesis, also known as text-to-speech (TTS) is one of the new key technologies in the artificial intelligence domain. It provides the capabilities to generate human-like voices from text input dynamically. TTS can be applied in a variety of purposes and tied closely … Read more

Generalizing Your Model: An Example With EfficientNetV2 and Cats & Dogs | by Daniel Reiff | May, 2022

Generalizing Your Model: An Example With EfficientNetV2 and Cats & Dogs |  by Daniel Reiff |  May, 2022

Consider this scenario. You are using the new fancy state-of-the-art CNN network architecture, EfficientNetV2, to train an image classifier. You’ve achieved impressive training accuracy (> 95%) but the model is not learning evaluation samples nearly as well as training samples. As machine learning engineers, we understand that our models are only as good as they … Read more

Machines do not have empathy, data scientists should | by Bahar Salehi | May, 2022

Machines do not have empathy, data scientists should |  by Bahar Salehi |  May, 2022

Empathy is an important step of problem-solving neglected by many data scientists. ML democratization may not be helping! Previously I wrote an article on how UX research and data science have very similar work processes and can complement each other to help with problem-solving and making informed decisions. In this article, I want to focus … Read more