Natural Language Annotation for Machine Learning
Build annotation guidelines, label language data and use evaluation results to improve an annotation project.
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AI annotation and evaluation, engineering, security and enterprise blockchain. Links open the author’s or publisher’s website in a new tab. Paid books require a purchase or subscription.
Build annotation guidelines, label language data and use evaluation results to improve an annotation project.
Combine human judgment with active learning, data annotation and quality control to improve machine learning systems.
Evaluate foundation models and application outputs, then make informed choices about prompts, retrieval and adaptation.
Connect training data, evaluation metrics and production monitoring to the goals of a machine learning application.
Inspect model behavior with feature importance, local explanations and methods for evaluating the explanations themselves.
Explore the practices that keep software maintainable over time, including code review, testing and collaboration.
Learn from the architectural decisions behind real open-source projects, from databases to compilers and developer tools.
Study virtualization, concurrency and persistence through clear explanations, exercises and systems projects.
Build small tools in Python to understand software design through working implementations and focused exercises.
Reason about storage, replication, transactions and distributed data systems by examining their architectural trade-offs.
A mathematical foundation for encryption, signatures, authentication and the security properties of cryptographic protocols.
Understand the cryptographic building blocks used in applications, secure communication and modern authentication systems.
Identify threats early and use structured threat modeling to guide security decisions throughout product development.
Learn how common web attacks work and how to defend applications through secure development practices.
Examine browser security models, web platform behavior and the design problems that shape application security.
Develop enterprise smart contracts and explore identity, access control and integration in Hyperledger Fabric applications.
Work through Fabric 2 network design, chaincode, security and the operational concerns of permissioned blockchain systems.
Compare enterprise platforms and study consensus, deployment models and architecture choices for business use cases.
Assess where blockchain creates business value and how organizations can develop networks and shared operating models.
Connect blockchain architecture to application development with enterprise use cases and implementation examples.
Service objectives, monitoring and the practice of running production systems.
Practical examples for applying SRE principles to everyday operations.
Designing and operating systems with security and reliability together.
Version control, branching, collaboration and the internals of Git.
An interactive textbook connecting deep learning concepts with runnable code.
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