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Production Machine Learning Systems

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Google Cloud Training

In this course, we explore the components and best practices for building high-performing ML systems in production environments. We cover considerations such as static and dynamic training and inference, distributed TensorFlow, and TPUs. This course focuses on the characteristics of effective ML systems beyond their predictive capabilities.

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What's inside

Syllabus

> Introduction to Advanced Machine Learning on Google Cloud
> This module previews the topics covered in the course and how to use Qwiklabs
... and ten others

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Reviews summary

Building production ml systems on gcp

According to learners, this course provides a largely useful introduction to the challenges and considerations when deploying machine learning models into production environments, particularly within the Google Cloud ecosystem. Students appreciate the practical focus and the inclusion of hands-on labs that reinforce the concepts covered in the lectures. While many find it a valuable overview covering topics like training strategies, inference methods, and performance considerations, some reviewers note that the course can feel high-level and occasionally lacks deep technical detail. It is generally seen as a solid starting point for understanding the production aspects of ML.

Career center

Learners who complete Production Machine Learning Systems will develop knowledge and skills that may be useful to these careers:
Machine Learning Engineer
Machine Learning Engineers are responsible for developing, deploying, and
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Austin
$178,000
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¥510,000
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Data Scientist
Data Scientists use machine learning and other statistical techniques to
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Austin
$171,000
Paris
€61,000
Tel Aviv
₪466,000
Shenzhen
¥505,000
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Software Engineer
Software Engineers design, develop, and maintain software systems. This course
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London
£95,000
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₪472,000
Shanghai
¥520,000
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Product Manager
Product Managers are responsible for defining the vision and roadmap for
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₪472,000
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Data Analyst
Data Analysts use data to identify trends and patterns. This course can help
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Austin
$90,000
Singapore
S$52,000
Shenzhen
¥257,000
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Business Analyst
Business Analysts use data to identify opportunities and solve problems. This
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Quantitative Analyst
Quantitative Analysts use mathematical and statistical techniques to analyze
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New York
$160,000
San Francisco
$202,000
Paris
€95,000
Shanghai
¥778,000
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Operations Research Analyst
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Shenzhen
¥167,000
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Risk Analyst
Risk Analysts use data to identify and assess risks. This course can help you
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Shenzhen
¥156,000
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Financial Analyst
Financial Analysts use data to analyze financial performance and make
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London
£87,000
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Marketing Analyst
Marketing Analysts use data to identify and target customers. This course can
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Singapore
S$70,000
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Sales Analyst
Sales Analysts use data to identify and close sales leads. This course can
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Berlin
€66,000
Tel Aviv
₪207,000
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Customer Success Manager
Customer Success Managers help customers get the most value from their
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San Francisco
$142,000
Berlin
€85,000
Singapore
S$128,000
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Technical Writer
Technical Writers create documentation for software and other technical
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User Experience Designer
User Experience Designers design products and services with a focus on the
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Austin
$105,000
Tel Aviv
₪223,000
Shanghai
¥400,000
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Reading list

We've selected nine books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Production Machine Learning Systems.
Data Science on the Google Cloud Platform
This book presents a collection of design
Cross-Lingual Word Embeddings
This book provides a comprehensive overview of
Probabilistic Machine Learning
This book provides a comprehensive overview of
Cyber Security
This book provides a comprehensive overview of
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