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General:
Name: Playboy Special Editions – Casting Calls – A First Look At Over 100 Sexy Girls
Format: pdf
Size: 8.17 MB
Book:
Title: Playboy Special Editions – Casting Calls – A First Look At Over 100 Sexy Girls.pdf
Author: jilanishanoor
Language: angielski
Year: 2021
Subjects: N/A
Publisher: Wydawnictwo: Packt Publishing
ISBN: 1800569009
Total pages: 36
Description:
AWS Certified Machine Learning Specialty: MLS-C01 Certification Guide
The AWS Certified Machine Learning Specialty exam tests your competency to perform machine learning (ML) on AWS infrastructure. This book covers the entire exam syllabus using practical examples to help you with your real-world ML projects on AWS.
Starting with an introduction to ML on AWS, you’ll learn the fundamentals of ML and explore important AWS services for artificial intelligence (AI). You’ll then see how to prepare data for ML and discover a wide variety of techniques for data manipulation and transformation for different types of variables. The book also shows you how to handle missing data and outliers and takes you through various ML tasks such as classification, regression, clustering, forecasting, anomaly detection, text mining, and image processing, along with the specific ML algorithms you need to know to pass the exam. Finally, you’ll explore model evaluation, optimization, and deployment and get to grips with deploying models in a production environment and monitoring them. By the end of this book, you’ll have gained knowledge of the key challenges in ML and the solutions that AWS has released for each of them, along with the tools, methods, and techniques commonly used in each domain of AWS ML.
Things you will learn:
Understand all four domains covered in the exam, along with types of questions, exam duration, and scoring Become well versed in ML terminologies, methodologies, frameworks, and the different AWS services for ML
Get to grips with data preparation and using AWS services for batch and real-time data processing
Explore the built-in ML algorithms in AWS and build and deploy your own models Evaluate ML models and tune hyperparameters
Deploy ML models with
the AWS infrastructure
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