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Total Size:
14.4 MB
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48616832817793611500510F37B5535A5A32AF5A
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June 25, 2025, 1:03 p.m.
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(Last updated: June 25, 2025, 1:04 p.m.)
| File | Size |
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| ['Cabianca D. AWS Certified Machine Learning Engineer Study Guide...MLA-C01)..2025.pdf'] | 0 bytes |
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51.8 MB
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2023-07-01
| Uploaded by indexFroggy | Size 51.8 MB | Health [ 12 /0 ] | Added 2023-07-01 |
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14.4 MB
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| Uploaded by andryold1 | Size 14.4 MB | Health [ 10 /13 ] | Added 2025-06-25 |
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SOURCE: Cabianca D. AWS Certified Machine Learning Engineer Study Guide...MLA-C01)..2025
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MEDIAINFO
Textbook in PDF format Prepare for the AWS Machine Learning Engineer exam smarter and faster and get job-ready with this efficient and authoritative resource In AWS Certified Machine Learning Engineer Study Guide: Associate (MLA-C01) Exam, veteran AWS Practice Director at Trace3—a leading IT consultancy offering AI, data, cloud and cybersecurity solutions for clients across industries—Dario Cabianca delivers a practical and up-to-date roadmap to preparing for the MLA-C01 exam. You'll learn the skills you need to succeed on the exam as well as those you need to hit the ground running at your first AI-related tech job. You'll learn how to prepare data for machine learning models on Amazon Web Services, build, train, refine models, evaluate model performance, deploy and secure your machine learning applications against bad actors. Inside the book - Complimentary access to the Sybex online test bank, which includes an assessment test, chapter review questions, practice exam, flashcards, and a searchable key term glossary - Strategies for selecting and justifying an appropriate machine learning approach for specific business problems and identifying the most efficient AWS solutions for those problems - Practical techniques you can implement immediately in an artificial intelligence and machine learning (AI/ML) development or data science role Perfect for everyone preparing for the AWS Certified Machine Learning Engineer — Associate exam, AWS Certified Machine Learning Engineer Study Guide is also an invaluable resource for those preparing for their first role in AI or data science, as well as junior-level practicing professionals seeking to review the fundamentals with a convenient desk reference
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