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Discover how combining scientific computing with machine learning accelerates simulators and enhances industrial modeling through differential equations and data-driven approaches.
Discover how to design and implement robust Model Predictive Control systems that handle parameter uncertainty effectively, with practical demonstrations using a single integrator system.
Master OpenAPI implementation in Julia for creating and consuming web APIs, including specification basics, service development, and client-side integration for efficient API management.
Discover how to streamline industrial modeling workflows using JuliaSim and JuliaHub, covering data management, version control, parallel computing, and team collaboration tools.
Discover how JuliaSim accelerates physical product development through advanced modeling, optimization, and simulation capabilities, featuring ModelingToolkit.jl and innovative solver improvements.
Master large-scale compute deployment in Julia, from structuring multi-core computations to building interactive web applications and dashboards with real-time monitoring capabilities.
Master parallel computing techniques in Julia, from SIMD and multi-threading to GPU programming, enhancing enterprise-level computational capabilities and performance optimization.
Master Julia performance optimization techniques using profiling tools, runtime tuning, and compilation strategies to significantly boost code efficiency and execution speed.
Master building secure and efficient production services in Julia, from prototyping to deployment, with emphasis on interactive data science and model implementation techniques.
Master GPU programming in Julia through CUDA-focused techniques, essential packages, and practical tools for accelerating applications and optimizing code performance on NVIDIA hardware.
Master PackageCompiler.jl to eliminate compilation overhead, create standalone executables, and optimize Julia package loading for enhanced performance and distribution.
Master time series machine learning in Julia using Flux to build powerful models that leverage diverse features for predictive analysis and data modeling.
Master SIMD optimization techniques in Julia to enhance computational performance through parallel processing and learn automatic and manual implementation methods for efficient data operations.
Explore advanced control design techniques for MIMO systems, from PID controller autotuning to nonlinear Model Predictive Control using JuliaSim's efficient simulation platform.
Master GPU application optimization in Julia through CUDA profiler tools and performance analysis techniques for efficient parallel computing implementation.
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