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AWS Certified Machine Learning - Specialty

Published by Pearson (April 28, 2024)

ISBN-13: 9780138283148

  • Course

$399.99

Product details

4.5 hours of video; Quizzes; Credly badging; 365-day course access

Includes

  • Prepare for the AWS Certified Machine Learning - Specialty exam
  • Identify and implement data ingestion solutions with Kinesis
  • Evaluate and deploy ML models

Language: English

Product Information

Learn the techniques and approaches to successfully pass the AWS Certified Machine Learning - Specialty Exam.

Getting the AWS Certified Machine Learning certification highlights your versatility as an ML engineer. Usually, ML engineers focus on handling data and building models, so if you know can use cloud tools, it makes you an even more valuable as an MLOps engineer. You'll be able to ingest your own data, get through the feature engineering process, train and evaluate models, and deploy them to where they will be consumed. This certification shows that you know how to do full-stack ML development.

In this course author Milecia McGregor shares a mix of slides, demonstrations in AWS, and hands-on exercises, along with some examples in Visual Studio with Python. It's just what you need to learn to pass the exam. It includes an overview of concepts with hands-on work using AWS tools like Kinesis and EMR.

Lesson 1: Data Engineering

Lesson 2: Exploratory Data Analysis

Lesson 3: Training Models

Lesson 4: Evaluating Models

Lesson 5: Machine Learning Implementation and Operations

Milecia McGregor is a software generalist who has worked in numerous areas of tech over the past decade. With a master's degree in mechanical and aerospace engineering, Milecia has accomplished many groundbreaking projects over the years, including Machine Learning (ML) work for human-computer interfaces on autonomous vehicles; front-end and back-end; data science; robotics; DevOps; cybersecurity; VR; and more. Milecia is also an international speaker in the tech community, with talks covering a variety of topics across multiple programming languages.

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