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Explore all talks and presentations from Code::Dive. Dive deep into the latest insights, research, and trends from the world's leading experts.
Explores C++ function failure reporting methods, comparing exceptions and error codes, and examines how C++17 features and the Outcome library impact failure handling approaches.
Insights on software engineering principles, code quality, and architecture from an electronic engineering perspective, offering a structured approach to understanding and improving programming practices.
Explore Visual Studio 2017's enhanced C++ development features, including cross-platform support, improved coding productivity, and CMake integration for a streamlined development experience.
Explore data-oriented design as an alternative to OOP in C++, focusing on practical examples from web browsers to demonstrate improved performance, scalability, and maintainability.
Exploring challenges and realities of code reuse in software development, drawing from 25 years of experience in test automation to provide insights on planning, cost, quality, and human factors.
Techniques for writing easily understandable code, focusing on function-level improvements to enhance readability, reviewability, and modifiability.
Explore Redux architecture through live coding, learning its core concepts and practical implementation for efficient application state management.
Explore the Salami Method for efficient cross-platform development, focusing on separating platform-specific code from core functionality to create maintainable, testable, and portable systems.
Explore type theory, category theory, and logic in functional programming, focusing on algebraic data types and their role in enhancing code reliability and expressiveness.
Explore the current state of Augmented Reality, its real-world applications, and future potential. Learn about different AR approaches, key players, and emerging technologies like AR Cloud.
Explore neural networks interactively in your browser with TensorFlow.js. Learn about applications, demos, and privacy-focused machine learning projects through hands-on examples and visualizations.
Exploring the unique challenges and approaches in machine learning programming from a software engineer's perspective, with insights on data handling, model development, and result interpretation.
Explore techniques to reduce OS noise and improve performance in multi-core processors using offload drivers, with a focus on Intel® Xeon Phi™ Processors.
Explore real-world Data Science projects, their business impacts, and methodologies. Gain insights into executing successful DS initiatives and structuring conclusions for practical applications.
Comprehensive exploration of FPGA technology, covering architecture, programming, and execution processes. Compares FPGAs to traditional processors and discusses their growing role as accelerators in various computing environments.
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