In the second course of the Practical Data Science Specialization, you will learn to automate a natural language processing task by building an end-to-end machine learning pipeline using Hugging Face’s highly-optimized implementation of the state-of-the-art BERT algorithm with Amazon SageMaker Pipelines. Your pipeline will first transform the dataset into BERT-readable features and store the features in the Amazon SageMaker Feature Store. It will then fine-tune a text classification model to the dataset using a Hugging Face pre-trained model, which has learned to understand the human language from millions of Wikipedia documents. Finally, your pipeline will evaluate the model’s accuracy and only deploy the model if the accuracy exceeds a given threshold.
Ce cours fait partie de la Spécialisation Practical Data Science on the AWS Cloud
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Spécialisation Practical Data Science on the AWS Clouddeeplearning.aiÀ propos de ce cours
Working knowledge of ML & Python, familiarity with Jupyter notebook & stat, completion of the Deep Learning & AWS Cloud Technical Essentials courses
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Essayez Coursera pour les affairesCe que vous allez apprendre
Store and manage machine learning features using a feature store
Debug, profile, tune and evaluate models while tracking data lineage and model artifacts
Compétences que vous acquerrez
- ML Pipelines and MLOps
- Model Training and Deployment with BERT
- Model Debugging and Evaluation
- Feature engineering and feature store
- Artifact and lineage tracking
Working knowledge of ML & Python, familiarity with Jupyter notebook & stat, completion of the Deep Learning & AWS Cloud Technical Essentials courses
Votre entreprise pourrait-elle bénéficier de la formation des employés à des compétences recherchées ?
Essayez Coursera pour les affaires
Offert par
Programme de cours : ce que vous apprendrez dans ce cours
Week 1: Feature Engineering and Feature Store
Week 2: Train, Debug, and Profile a Machine Learning Model
Week 3: Deploy End-To-End Machine Learning pipelines
Avis
- 5 stars71,90 %
- 4 stars17,35 %
- 3 stars9,09 %
- 2 stars0,82 %
- 1 star0,82 %
Meilleurs avis pour BUILD, TRAIN, AND DEPLOY ML PIPELINES USING BERT
Very Hands On Practical Information for the Industry
Very hands-on AWS BERT labs! Expecting more labs coming...
Week 3 lab gave twice error 'Failed' and 3rd time it went without an issue. This was quite frustrating. Overall, good class. Thx.
It is one of course with the exact content required for an working professional who is already working with AWS and want to leverage the benefits of sagemaker for their ML deployment tasks
À propos du Spécialisation Practical Data Science on the AWS Cloud
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