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This course explores how to use the machine learning (ML) pipeline to solve a real business problem in a project-based learning environment. Students will lea> about each phase of the pipeline from instructor presentations and demonstrations and then apply that knowledge to complete a project solvi...

Audience This course is intended for: Developers Solutions Architects Data Engineers Anyone with little to no experience with ML and wants to lea> about the ML pipeline using Amazon SageMaker...

Goals In this course, you will lea> how to: Select and justify the appropriate ML approach for a given business problem Use the ML pipeline to solve a specific business problem Train, evaluate, deploy, and tune an ML model using Amazon SageMaker Describe some of the best practices for desi...

Prerequisites We recommend that attendees of this course have: Basic knowledge of Python programming language Basic understanding of AWS Cloud infrastructure (Amazon S3 and Amazon CloudWatch) Basic experience working in a Jupyter notebook environment Study materials Amazon Web Services authorized e-book included.

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Zpět ke kurzu

• The Machine Learning Pipeline on AWS
• DataScript s.r.o.
• Jednotlivé termíny podobných školení
• Dotaz ke kurzu

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Platební podmínky pro účast na kurzu

Objednavateli bude zaslána závazná přihláška k podpisu. Poté bude účastník na školení registrován. Objednavatel uhradí částku kurzovného za výše uvedeného posluchače na základě faktury vystavené poskytovatelem.