Author: Stephanie Glen The lifecycle of data travels through six phases: The lifecycle “wheel” isn’t set in stone. While it’s common to move through the […] Read More
Author: Charles Durfee
Computer Science student with a passion for data science and artificial intelligence.
Author: Adam Conner-Simons | CSAIL These days, nearly all the artificial intelligence-based products in our lives rely on “deep neural networks” that automatically learn to […] Read More
Author: Machine learning for .NET devs: ML.NET goes GA ZDNet NET developers, across platforms, now have access to machine learning from their home turf. Microsoft Automated […] Read More
Author: /u/AutoModerator Welcome to this week’s entering & transitioning thread! This thread is for any questions about getting started, studying, or transitioning into the data […] Read More
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Author: Vincent Granville Monday newsletter published by Data Science Central. Previous editions can be found here. The contribution flagged with a + is our selection for […] Read More
Author: Jason Brownlee Deep learning neural networks are generally opaque, meaning that although they can make useful and skillful predictions, it is not clear how […] Read More
Author: Vincent Granville This crash course features a new fundamental statistics theorem — even more important than the central limit theorem — and a new […] Read More
Author: Microsoft Launches a Drag-and-Drop Machine Learning Tool WLS Microsoft makes a push to simplify machine learning TechCrunch AI Weekly: Microsoft, machine learning framework interoperability, and ONNX VentureBeat […] Read More
Author: Dan Clark In recent years, XGBoost algorithm has gained enormous popularity in academic as well as business world. We outline some of the reasons […] Read More