While Excel is ubiquitous, I prefer Python for my data analysis. Spreadsheets are great for formatting data, but it's Python that's allowed me to build my own super calculator out of regular Python ...

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As an emerging technology in the field of artificial intelligence (AI), graph neural networks (GNNs) are deep learning models designed to process graph-structured data. Currently, GNNs are effective ...

Pypst helps you dynamically generate Typst code directly in Python. No manual string manipulation required. It has two major use cases: Generating full Typst documents to be rendered as PDFs ...

The pace and intensity of filings show us something important: this isn’t a passing trend. It’s a structural shift in how the plaintiffs’ bar sees opportunity, and it is reshaping the risk landscape ...

Graphs and data visualizations are all around us—charting our steps, our election results, our favorite sports teams’ stats, and trends across our world. But too often, people glance at a graph ...

Can the users of financial statements and annual reports rely upon the charts in them for accuracy? A sample of 50 public companies’ yearly reports collected by the author found that 86% had at least ...

Rajiv Shesh is the Chief Revenue Officer at HCLSoftware where he leads revenue growth & customer advocacy for Products & Platforms division. What’s really powering AI? High-quality data—foundational ...

Abstract: Graph Convolutional Networks (GCNs) have been widely studied for attribute graph data learning. In many applications, graph node attributes/features may contain various kinds of noises, such ...