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Machine Learning with Spark on Google Cloud Dataproc

Google Cloud Training

This is a self-paced lab that takes place in the Google Cloud console.

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This is a self-paced lab that takes place in the Google Cloud console.

In this lab you will learn how to implement logistic regression using a machine learning library for Apache Spark running on a Google Cloud Dataproc cluster to develop a model for data from a multivariable dataset.

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What's inside

Syllabus

Machine Learning with Spark on Google Cloud Dataproc

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Develops machine learning and Apache Spark skills, which are core in data science and data analysis
Builds a strong foundation for learners new to machine learning and Apache Spark
Takes a practical approach by featuring hands-on labs and interactive materials
Taught by Google Cloud Training, recognized for their expertise in cloud computing and machine learning
Requires learners to come in with some basic understanding of machine learning and programming

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Save Machine Learning with Spark on Google Cloud Dataproc to your list so you can find it easily later:
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Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Machine Learning with Spark on Google Cloud Dataproc with these activities:
Review Logistic Regression Concepts
Reviewing basic logistic regression concepts will help you better understand the algorithms and techniques taught in this course.
Browse courses on Logistic Regression
Show steps
  • Read the documentation for Logistic Regression in Apache Spark MLlib.
  • Go through a few examples of Logistic Regression in Spark.
Read Machine Learning with Apache Spark
Reading this book will provide you with a comprehensive understanding of machine learning algorithms and their implementation in Apache Spark.
View Advanced Analytics with PySpark: Patterns for... on Amazon
Show steps
  • Purchase or borrow a copy of the book.
  • Read the book thoroughly.
  • Complete the exercises and examples provided in the book.
Join a study group or discussion forum on Logistic Regression
Engaging with peers through study groups or discussion forums can provide you with different perspectives and insights.
Show steps
  • Find a study group or discussion forum on Logistic Regression.
  • Participate in the discussions and share your knowledge.
  • Ask questions and seek help from other members of the group.
Three other activities
Expand to see all activities and additional details
Show all six activities
Follow a tutorial on Logistic Regression with Spark
Following a tutorial will provide you with a step-by-step guide to implementing logistic regression with Spark, giving you hands-on experience.
Show steps
  • Find a tutorial on Logistic Regression with Spark.
  • Follow the tutorial step-by-step.
  • Complete the exercises and examples provided in the tutorial.
Solve practice problems on Logistic Regression
Solving practice problems will help you apply your knowledge and identify areas where you need more practice.
Show steps
  • Find a set of practice problems on Logistic Regression.
  • Solve the problems on your own.
  • Check your answers and identify areas where you need more practice.
Attend a workshop on Logistic Regression with Spark
Attending a workshop will provide you with focused training and an opportunity to interact with experts in the field.
Show steps
  • Find a workshop on Logistic Regression with Spark.
  • Register for the workshop.
  • Attend the workshop and actively participate in the sessions.

Career center

Learners who complete Machine Learning with Spark on Google Cloud Dataproc will develop knowledge and skills that may be useful to these careers:
Machine Learning Engineer
Machine learning engineers are responsible for developing, deploying, and maintaining machine learning models. The Machine Learning with Spark on Google Cloud Dataproc course will be a great starting point for learning the fundamentals of machine learning, as well as how to apply machine learning to real-world problems. The course will help engineers gain the skills needed to design, build, and evaluate machine learning models, as well as how to deploy and manage them in a production environment.
See salaries and explore the career path for Machine Learning Engineer
Data Scientist
Data scientists are responsible for collecting, analyzing, and interpreting data. The Machine Learning with Spark on Google Cloud Dataproc course is an excellent way to help data scientists get started with machine learning. The course provides a solid foundation in the basics of machine learning, as well as how to apply machine learning to real-world problems. The course will teach data scientists how to use Spark to build and test machine learning models, as well as how to evaluate the performance of those models.
See salaries and explore the career path for Data Scientist
Data Analyst
Data analysts may enjoy the Machine Learning with Spark on Google Cloud Dataproc course since it will aid them in performing complex data analysis. The course teaches skills such as data preparation, feature engineering, model creation, and evaluation, all of which are essential for data analysts. In particular, the course's emphasis on machine learning and its application to real-world problems will enable data analysts to expand their skillset and advance their careers in the booming field of big data.
See salaries and explore the career path for Data Analyst
Quantitative Analyst
Quantitative analysts are responsible for using mathematical and statistical models to analyze data. The Machine Learning with Spark on Google Cloud Dataproc course can help quantitative analysts learn how to use Spark to build and test machine learning models. The course will teach quantitative analysts how to use Spark to process and store data, as well as how to use Spark to build and test machine learning models.
See salaries and explore the career path for Quantitative Analyst
Statistician
Statisticians are responsible for collecting, analyzing, and interpreting data. The Machine Learning with Spark on Google Cloud Dataproc course can help statisticians learn how to use Spark to analyze data and identify trends. The course will teach statisticians how to use Spark to process and store data, as well as how to use Spark to build and test machine learning models.
See salaries and explore the career path for Statistician
Data Engineer
Data engineers are responsible for designing, building, and maintaining the infrastructure that supports data analysis. The Machine Learning with Spark on Google Cloud Dataproc course can help data engineers learn how to use Spark to build and manage the infrastructure needed for machine learning. The course will teach data engineers how to use Spark to process and store data, as well as how to use Spark to build and test machine learning models.
See salaries and explore the career path for Data Engineer
Software Engineer
Software engineers are responsible for designing, developing, and maintaining software applications. The Machine Learning with Spark on Google Cloud Dataproc course can help software engineers learn how to use Spark to build and deploy machine learning models. The course will teach software engineers how to use Spark to process and store data, as well as how to use Spark to build and test machine learning models.
See salaries and explore the career path for Software Engineer
Operations Research Analyst
Operations research analysts are responsible for using mathematical and statistical models to solve business problems. The Machine Learning with Spark on Google Cloud Dataproc course can help operations research analysts learn how to use Spark to build and test machine learning models. The course will teach operations research analysts how to use Spark to process and store data, as well as how to use Spark to build and test machine learning models.
See salaries and explore the career path for Operations Research Analyst
Fraud Analyst
Fraud analysts are responsible for identifying and investigating fraudulent activities. The Machine Learning with Spark on Google Cloud Dataproc course can help fraud analysts learn how to use Spark to analyze data and identify fraudulent activities. The course will teach fraud analysts how to use Spark to process and store data, as well as how to use Spark to build and test machine learning models.
See salaries and explore the career path for Fraud Analyst
Business Analyst
Business analysts are responsible for analyzing business data to identify trends and opportunities. The Machine Learning with Spark on Google Cloud Dataproc course can help business analysts learn how to use Spark to analyze data and identify trends. The course will teach business analysts how to use Spark to process and store data, as well as how to use Spark to build and test machine learning models.
See salaries and explore the career path for Business Analyst
Financial Analyst
Financial analysts are responsible for analyzing financial data to identify investment opportunities. The Machine Learning with Spark on Google Cloud Dataproc course can help financial analysts learn how to use Spark to analyze financial data and identify investment opportunities. The course will teach financial analysts how to use Spark to process and store data, as well as how to use Spark to build and test machine learning models.
See salaries and explore the career path for Financial Analyst
Risk Analyst
Risk analysts are responsible for identifying and assessing risks. The Machine Learning with Spark on Google Cloud Dataproc course can help risk analysts learn how to use Spark to analyze data and identify risks. The course will teach risk analysts how to use Spark to process and store data, as well as how to use Spark to build and test machine learning models.
See salaries and explore the career path for Risk Analyst
Security Analyst
Security analysts are responsible for identifying and mitigating security risks. The Machine Learning with Spark on Google Cloud Dataproc course can help security analysts learn how to use Spark to analyze data and identify security risks. The course will teach security analysts how to use Spark to process and store data, as well as how to use Spark to build and test machine learning models.
See salaries and explore the career path for Security Analyst
Compliance Analyst
Compliance analysts are responsible for ensuring that organizations comply with laws and regulations. The Machine Learning with Spark on Google Cloud Dataproc course can help compliance analysts learn how to use Spark to analyze data and identify compliance risks. The course will teach compliance analysts how to use Spark to process and store data, as well as how to use Spark to build and test machine learning models.
See salaries and explore the career path for Compliance Analyst
Data Visualization Analyst
Data visualization analysts are responsible for creating visualizations that help people understand data. The Machine Learning with Spark on Google Cloud Dataproc course can help data visualization analysts learn how to use Spark to create visualizations. The course will teach data visualization analysts how to use Spark to process and store data, as well as how to use Spark to build and test machine learning models.
See salaries and explore the career path for Data Visualization Analyst

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 Machine Learning with Spark on Google Cloud Dataproc.
Cover image
Learning Spark
Save
This comprehensive guide to Apache Spark, covering core concepts, APIs, and best practices for building scalable and efficient data pipelines and machine learning models.
Learning Spark: Lightning-Fast Big Data Analysis
Paperback
$$
Cover image
Advanced Analytics with PySpark
Save
Explores advanced analytics techniques, such as graph processing, natural language processing, and deep learning, using Spark.
Advanced Analytics with PySpark: Patterns for...
Paperback
$$
Advanced Analytics with PySpark
Kindle Edition
$$
Cover image
Probabilistic Machine Learning
Save
Provides a comprehensive overview of machine learning from a probabilistic perspective. It valuable resource for anyone who wants to learn more about the theoretical foundations of machine learning.
Probabilistic Machine Learning: Advanced Topics...
Hardcover
$$$$
Pattern Recognition and Machine Learning
Save
Provides a comprehensive overview of pattern recognition and machine learning. It valuable resource for anyone who wants to learn more about the theoretical foundations of pattern recognition and machine learning.
Pattern Recognition and Machine Learning...
Hardcover
$$$
Pattern Recognition and Machine Learning...
Paperback
$$$
Pattern Recognition and Machine Learning (text...
Unknown Binding
$$$$
Cover image
Introduction to Machine Learning with Python
Save
Provides a comprehensive overview of machine learning with Python. It valuable resource for anyone who wants to learn more about machine learning with Python.
Introduction to Machine Learning with Python: A...
Kindle Edition
$$
Cover image
Machine Learning with R
Save
Provides a comprehensive overview of machine learning with R. It valuable resource for anyone who wants to learn more about machine learning with R.
Machine Learning with R - Fourth Edition: Learn...
Paperback
$$
Machine Learning with R - Second Edition: Expert...
Kindle Edition
$$
Machine Learning with R - Third Edition: Expert...
Paperback
$$
(Italiano) Machine Learning con R: Conoscere le tecniche per...
Kindle Edition
$$
R: Unleash Machine Learning Techniques
Kindle Edition
$$$
Machine Learning with R: Learn How to Use R to...
Paperback
$$
(中文) Machine learning and R language (3rd edition of the...
Paperback
$$
Cover image
MACHINE LEARNING
Save
Provides a comprehensive overview of machine learning from an algorithmic perspective. It valuable resource for anyone who wants to learn more about the algorithmic foundations of machine learning.
Machine Learning: An Algorithmic Perspective,...
Hardcover
$$$
Machine Learning: An Algorithmic Perspective...
Paperback
$$
An Algorithmic Perspective on Machine Learning (2nd...
Paperback
$$$
Machine Learning: An Algorithmic Perspective,...
Kindle Edition
$$$
Cover image
Mathematics for Machine Learning
Save
Provides a comprehensive overview of the mathematics for machine learning. It valuable resource for anyone who wants to learn more about the mathematical foundations of machine learning.
Mathematics for Machine Learning
Kindle Edition
$$
Cover image
Machine Learning with PyTorch and Scikit-Learn
Save
Provides a comprehensive overview of machine learning with Python. It valuable resource for anyone who wants to learn more about machine learning with Python.
Machine Learning with PyTorch and Scikit-Learn:...
Kindle Edition
$$

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Course image
Effort
1 hour 30 minutes
Level
Intermediate
Via
Coursera
Institution
Google Cloud
Instructor
Google Cloud Training
Language
English
Good to know
Develops machine learning and Apache Spark skills, which are core in data science and data analysis
Builds a strong foundation for learners new to machine learning and Apache Spark
Takes a practical approach by featuring hands-on labs and interactive materials
Taught by Google Cloud Training, recognized for their expertise in cloud computing and machine learning
Requires learners to come in with some basic understanding of machine learning and programming
Share and help others discover this course.
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