Certificate in AI Performance Analysis: Results-Oriented
-- ViewingNowThe Certificate in AI Performance Analysis is a results-oriented course designed to equip learners with essential skills in AI performance analysis. In today's data-driven world, the demand for AI professionals has never been higher.
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โข Introduction to AI Performance Analysis: Understanding the basics of AI performance analysis, its importance, and the methodologies involved.
โข Performance Metrics for AI Systems: Identifying and understanding the key performance metrics for AI systems, including accuracy, precision, recall, and F1 score.
โข Profiling AI Systems: Learning how to profile AI systems to identify performance bottlenecks, using tools such as TensorBoard, Prometheus, and Grafana.
โข Optimizing AI Algorithms: Techniques for optimizing AI algorithms for better performance, including pruning, quantization, and knowledge distillation.
โข Scaling AI Systems: Strategies for scaling AI systems, including horizontal and vertical scaling, distributed computing, and containerization.
โข AI Performance Analysis Tools: Hands-on experience with popular AI performance analysis tools, including TensorFlow Profiler, Nsight, and PySnooper.
โข Benchmarking AI Systems: Techniques for benchmarking AI systems to compare performance, including using standard benchmarks and creating custom benchmarks.
โข AI Performance Analysis Best Practices: Best practices for AI performance analysis, including monitoring, testing, and validation.
โข AI Performance Analysis in Real-world Scenarios: Applying AI performance analysis techniques to real-world scenarios and use cases, including computer vision, natural language processing, and recommendation systems.
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