Chapters and Articles
IBM Blockchain experts define the overall blockchain technology landscape and address the trust divide between an enterprise (permissioned) blockchain and a public, permissionless blockchain.
It’s important to balance stakeholder expectations when you scope a project, and good causal inference can take time. Data scientists Andrew and Adam Kelleher help you develop the tools you need to do causal inference.
Discusses common issues, solutions, and best practices for interoperability with Java.
This chapter describes how you can use the tidyr (“tidy-er”) package to effectively transform your data into an appropriate shape for analysis and visualization.
Well-known educator Matt Bishop discusses informal techniques for writing programs that enforce security policies.
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