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  • Book Overview & Buying The Self-Taught Cloud Computing Engineer
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The Self-Taught Cloud Computing Engineer

The Self-Taught Cloud Computing Engineer

By : Dr. Logan Song
5 (180)
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The Self-Taught Cloud Computing Engineer

The Self-Taught Cloud Computing Engineer

5 (180)
By: Dr. Logan Song

Overview of this book

As cloud computing continues to revolutionize IT, professionals face the challenge of keeping up with rapidly evolving technologies. This book provides a clear roadmap for mastering cloud concepts, developing hands-on expertise, and obtaining professional certifications, making it an essential resource for those looking to advance their careers in cloud computing. Starting with a focus on the Amazon cloud, you’ll be introduced to fundamental AWS cloud services, followed by advanced AWS cloud services in the domains of data, machine learning, and security. Next, you’ll build proficiency in Microsoft Azure cloud and Google Cloud Platform (GCP) by examining the common attributes of the three clouds, differentiating their unique features, along with leveraging real-life cloud project implementations on these cloud platforms. Through hands-on projects and real-world applications, you’ll gain the skills needed to work confidently across different cloud platforms. The book concludes with career development guidance, including certification paths and industry insights to help you succeed in the cloud computing landscape. Walking through this cloud computing book, you’ll systematically establish a robust footing in AWS, Azure, and GCP, and emerge as a cloud-savvy professional, equipped with cloud certificates to validate your skills.
Table of Contents (24 chapters)
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1
Part 1: Learning about the Amazon Cloud
9
Part 2:Comprehending GCP Cloud Services
14
Part 3:Mastering Azure Cloud Services
19
Part 4:Developing a Successful Cloud Career

Amazon Machine Learning Services

We discussed cloud databases and big data analytics in previous chapters. Part of the data analytics spectrum, machine learning (ML) involves building models or algorithms that enable computers to analyze and learn from data, identify patterns, relationships, and trends that can be used to make predictions or decisions.

Cloud-based ML platforms provide a range of tools and services to support ML workflows of data preparation, feature engineering, model training, tuning, and deployment. Cloud ML can be used for computer vision, natural language processing (NLP), and many other predictive analytics tasks. The Amazon cloud provides platforms for engineers and data scientists to develop ML models from end to end. In this chapter, we will discuss the following topics:

  • ML basics: What is ML? What are the objectives of ML? What problems can be solved using ML? What are some basic ML problems?
  • Amazon SageMaker: A fully managed AWS ML service...
CONTINUE READING
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Tech Concepts
36
Programming languages
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The Self-Taught Cloud Computing Engineer
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