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  • Book Overview & Buying AWS Certified Machine Learning - Specialty (MLS-C01) Certification Guide
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AWS Certified Machine Learning - Specialty (MLS-C01) Certification Guide

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

By : Nanda, Moura
4.6 (22)
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AWS Certified Machine Learning - Specialty (MLS-C01) Certification Guide

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

4.6 (22)
By: Nanda, Moura

Overview of this book

The 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.
Table of Contents (13 chapters)
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Image processing

Image processing is a very popular topic in machine learning. The idea is pretty self-explanatory: creating models that can analyze images and make inferences on top of them. By inference, you can understand this as detecting objects in an image, classifying images, and so on.

AWS offers a set of built-in algorithms you can use to train image processing models. In the next few sections, you will have a look at those algorithms.

Image classification algorithm

As the name suggests, the image classification algorithm is used to classify images using supervised learning. In other words, it needs a label within each image. It supports multi-label classification.

The way it operates is simple: during training, it receives an image and its associated labels. During inference, it receives an image and returns all the predicted labels. The image classification algorithm uses a CNN (ResNet) for training. It can either train the model from scratch or take advantage...

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