Optimize ML Models and Deploy Human-in-the-Loop Pipelines
https://www.coursera.org/learn/ml-models-human-in-the-loop-pipelines?specialization=practical-data-science
In the third course of the Practical Data Science Specialization, you will learn a series of performance-improvement and cost-reduction techniques to automatically tune model accuracy, compare prediction performance, and generate new training data with human intelligence. After tuning your text classifier using Amazon SageMaker Hyper-parameter Tuning (HPT), you will deploy two model candidates into an A/B test to compare their real-time prediction performance and automatically scale the winning model using Amazon SageMaker Hosting. Lastly, you will set up a human-in-the-loop pipeline to fix misclassified predictions and generate new training data using Amazon Augmented AI and Amazon SageMaker Ground Truth.
Categoria: Data Science
Subcategoria: Machine Learning
Tipo de Curso: Course
Habilidades: Human-in-the-Loop Pipelines,Distributed Model Training and Hyperparameter Tuning,Cost Savings and Performance Improvements,A/B Testing and Model Deployment,Data Labeling at Scale,
Idioma: English
Subtitulos: English
Rating: 4.7stars
Vistas: 93
Sitio Web: Coursera
Duracion: Approx. 10 hours to complete
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