Google Cloud Professional Machine Learning Engineer Cert Prep: 4 Developing ML Models faq

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This course, part of the Google Professional Machine Learning Engineer certification prep series, equips you with the skills to design, build, and deploy machine learning models using Google Cloud technologies, with a focus on topics like model development, TensorFlow, evaluation metrics, transfer learning, and model scaling for real-world applications.

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Go to class

Course Feature

costCost:

Free Trial

providerProvider:

LinkedIn Learning

certificateCertificate:

Paid Certification

languageLanguage:

English

start dateStart Date:

Released: 6/16/2023

Course Overview

❗The content presented here is sourced directly from LinkedIn Learning platform. For comprehensive course details, including enrollment information, simply click on the 'Go to class' link on our website.

Updated in [September 06th, 2023]

(Please Note that this content is from LinkedIn Learning)
The Google Professional Machine Learning Engineer certification demonstrates your ability to design, build, and deploy machine learning models for real-world business challenges using Google Cloud technologies. In this fourth course of the certification prep series, instructor Noah Gift covers topics related to machine learning model development. He guides you through building models with TensorFlow, clarifies concepts like overfitting versus underfitting, and explains the selection of appropriate evaluation metrics. Noah also delves into model training, highlighting the advantages of transfer learning. Additionally, you'll learn about scaling model training and serving, including building a microservice and deploying it with Rust on Google App Engine.

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