Understanding functional and technical aspects of AWS Certified Machine Learning Specialty Exam Data Engineering

The following will be dicussed here:

• Identify and implement a data-transformation solution
• Create data repositories for machine learning
• Identify and implement a data-ingestion solution

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Recommended Experience

Before registering for the AWS Certified Machine Learning – Specialty exam, the applicant should ensure meeting some prerequisites as stated by the vendor. First, working experience of 1-2 years in running ML workloads as well as their development and architecting on AWS cloud is a must for the candidate. Moreover, it is recommended to have practical skills in executing the hyperparameter optimization, deep learning and ML frameworks, and operational and model-training best practices for AWS Machine learning.

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Introduction to AWS Certified Machine Learning Specialty Exam

The AWS Certified Machine Learning Exam - Special Exam (MLS-C01) is designed for people who have a development or data science function. This exam validates a candidate's ability to create, train, adapt and implement machine learning (ML) models using the AWS cloud. Validation of a candidate's ability to design, implement, implement and maintain ML solutions for certain business problems. It will validate the candidate's ability to: Select and justify the appropriate LD approach for a given business problem. Identify the appropriate AWS services to implement ML solutions. Design and implement scalable, economic, reliable and safe ML solutions.

The AWS Machine Learning Specialty certification is designed for developers and data scientists who want to enhance their skills in using machine learning via the AWS platform.

Reference: https://d1.awsstatic.com/training-and-certification/docs-ml/AWS%20Certified%20Machine%20Learning%20-%20Specialty_Exam%20Guide%20(1).pdf

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