Languages
PyTorch tensors, neural networks and Autograd: an introduction
This guide is designed to demystify PyTorch's core components, providing you with a solid understanding of how it empowers the creation and training of sophisticated machine learning models.
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Python Machine Learning: Care & Quality for Developers
This post will discuss machine learning (ML) in Python, examining the unique considerations for application developers as AI's role in everyday software continues to expand.
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Deploying SonarQube on Kubernetes with Helm Charts
By using a Helm Chart to deploy SonarQube Server, teams can quickly provision a production-ready SonarQube Server instance with minimal configuration while adopting best practices for scalability, security, and maintainability.
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Securing Go Applications With SonarQube: Real-World Examples
Take a deep dive into some vulnerabilities in Go applications and understand how SonarQube Cloud helps developers detect and mitigate them during the development cycle.
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Java24: Go deeper on parsing Java class files and broader with Stream gatherers
Version 24 version introduces several new language features which collectively simplify code, and provide powerful tools for bytecode manipulation and advanced stream processing.
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Java 23: Embrace the new era of code comments
We’ve covered Java 22, and are now getting into Java 23, which introduces several new language features. We’ll focus on enhancing documentation, and how to leverage the new features with simple examples.
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