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AWS Certified Machine Learning - Specialty (MLS-C01) Certification Guide - Somanath Nanda, Weslley Moura

AWS Certified Machine Learning - Specialty (MLS-C01) Certification Guide

The ultimate guide to passing the MLS-C01 exam on your first attempt
Buch | Softcover
342 Seiten
2024 | 2nd Revised edition
Packt Publishing Limited (Verlag)
978-1-83508-220-1 (ISBN)
CHF 59,30 inkl. MwSt
Prepare confidently for the AWS MLS-C01 certification with this comprehensive and up-to-date exam guide, accompanied by web-based tools such as mock exams, flashcards, and exam tips

Key Features

Gain proficiency in AWS machine learning services to excel in the MLS-C01 exam
Build model training and inference pipelines and deploy machine learning models to the AWS cloud
Practice on the go with the mobile-friendly bonus website, accessible with the book
Purchase of the print or Kindle book includes a free PDF eBook

Book DescriptionThe AWS Certified Machine Learning Specialty (MLS-C01) exam evaluates your ability to execute machine learning tasks on AWS infrastructure. This comprehensive book aligns with the latest exam syllabus, offering practical examples to support your real-world machine learning projects on AWS. Additionally, you'll get lifetime access to supplementary online resources, including mock exams with exam-like timers, detailed solutions, interactive flashcards, and invaluable exam tips, all accessible across various devices—PCs, tablets, and smartphones.
Throughout the book, you’ll learn data preparation techniques for machine learning, covering diverse methods for data manipulation and transformation across different variable types. Addressing challenges such as missing data and outliers, the book guides you through an array of machine learning tasks including classification, regression, clustering, forecasting, anomaly detection, text mining, and image processing, accompanied by requisite machine learning algorithms essential for exam success. The book helps you master the deployment of models in production environments and their subsequent monitoring.
Equipped with insights from this book and the accompanying mock exams, you'll be fully prepared to achieve the AWS MLS-C01 certification.What you will learn

Identify ML frameworks for specific tasks
Apply CRISP-DM to build ML pipelines
Combine AWS services to build AI/ML solutions
Apply various techniques to transform your data, such as one-hot encoding, binary encoder, ordinal encoding, binning, and text transformations
Visualize relationships, comparisons, compositions, and distributions in the data
Use data preparation techniques and AWS services for batch and real-time data processing
Create training and inference ML pipelines with Sage Maker
Deploy ML models in a production environment efficiently

Who this book is forThis book is designed for both students and professionals preparing for the AWS Certified Machine Learning Specialty exam or enhance their understanding of machine learning, with a specific emphasis on AWS. Familiarity with machine learning basics and AWS services is recommended to fully benefit from this book.

Somanath has 10 years of working experience in IT industry which includes Prod development, Devops, Design and architect products from end to end. He has also worked at AWS as a Big Data Engineer for about 2 years. Weslley Moura has been developing data products for the past decade. At his recent roles, he has been influencing data strategy and leading data teams into the urban logistics and blockchain industries.

Table of Contents

Machine Learning Fundamentals
AWS Services for Data Storage
AWS Services for Data Migration and Processing
Data Preparation and Transformation
Data Understanding and Visualization
Applying Machine Learning Algorithms
Evaluating and Optimizing Models
AWS Application Services for AI/ML
Amazon SageMaker Modeling
Model Deployment

Erscheinungsdatum
Verlagsort Birmingham
Sprache englisch
Maße 191 x 235 mm
Themenwelt Mathematik / Informatik Informatik Netzwerke
Informatik Software Entwicklung User Interfaces (HCI)
Informatik Theorie / Studium Künstliche Intelligenz / Robotik
Informatik Weitere Themen Zertifizierung
ISBN-10 1-83508-220-3 / 1835082203
ISBN-13 978-1-83508-220-1 / 9781835082201
Zustand Neuware
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