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DeepLearning.AI vía Coursera
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Machine Learning Modeling Pipelines in Production

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  • Week 1: Neural Architecture Search
    • Learn how to effectively search for the best model that will scale for various serving needs while constraining model complexity and hardware requirements.
  • Week 2: Model Resource Management Techniques
    • Learn how to optimize and manage the compute, storage, and I/O resources your model needs in production environments during its entire lifecycle.
  • Week 3: High-Performance Modeling
    • Implement distributed processing and parallelism techniques to make the most of your computational resources for training your models efficiently.
  • Week 4: Model Analysis
    • Use model performance analysis to debug and remediate your model and measure robustness, fairness, and stability.
  • Week 5: Interpretability
    • Learn about model interpretability - the key to explaining your model’s inner workings to laypeople and expert audiences and how it promotes fairness and helps address regulatory and legal requirements for different use cases.