We may earn an affiliate commission when you visit our partners.
Google Cloud Training
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.
Register for this course and see more details by visiting:
OpenCourser.com/course/91i5qd/machine
What's inside
Syllabus
Machine Learning with Spark on Google Cloud Dataproc
Good to know
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
Save this course
Save Machine Learning with Spark on Google Cloud Dataproc to your list so you can find it easily later:
Save
Save
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
Show steps
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
Show steps
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
Show steps
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
Show steps
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
Show steps
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
Show steps
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.
Review Logistic Regression Concepts
Show steps
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
Show steps
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
Show steps
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
Show steps
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
Show steps
Engaging with peers through study groups or discussion forums can provide you with different perspectives and insights.
Show steps
Show steps
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
Show steps
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
Show steps
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
Show steps
Solving practice problems will help you apply your knowledge and identify areas where you need more practice.
Show steps
Show steps
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
Show steps
Attending a workshop will provide you with focused training and an opportunity to interact with experts in the field.
Show steps
Show steps
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 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.
Data Scientist
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.
Data Analyst
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.
Quantitative 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.
Statistician
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.
Data Engineer
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.
Software 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.
Operations Research Analyst
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.
Fraud 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.
Business 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.
Financial 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.
Risk 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.
Security 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.
Compliance 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.
Data Visualization 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.
For more career information including salaries, visit:
OpenCourser.com/course/91i5qd/machine
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.
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.
Explores advanced analytics techniques, such as graph processing, natural language processing, and deep learning, using Spark.
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.
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.
Provides a comprehensive overview of machine learning with Python. It valuable resource for anyone who wants to learn more about machine learning with Python.
Provides a comprehensive overview of machine learning with R. It valuable resource for anyone who wants to learn more about machine learning with R.
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.
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.
Provides a comprehensive overview of machine learning with Python. It valuable resource for anyone who wants to learn more about machine learning with Python.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/91i5qd/machine
Share
Similar courses
Here are nine courses similar to
Machine Learning with Spark on Google Cloud Dataproc.
Prisma Cloud Host Defender Auto Deploy from a SaaS Portal
OpenCourser.com/course/v89fa2/prisma
Prisma Cloud Host Defender Auto Deploy from a SaaS Portal
Eventarc for Cloud Run
OpenCourser.com/course/dgzmfz/eventarc
Eventarc for Cloud Run
Getting Started with Splunk Cloud GDI on Google Cloud
OpenCourser.com/course/ec3k53/getting
Getting Started with Splunk Cloud GDI on Google Cloud
Online Data Migration to Cloud Spanner using Striim
OpenCourser.com/course/z9b0jm/online
Online Data Migration to Cloud Spanner using Striim
Consuming Customer Specific Datasets from Data Sharing Partners using BigQuery
OpenCourser.com/course/up4l9s/consuming
Consuming Customer Specific Datasets from Data Sharing...
Managing NetApp Cloud Volumes ONTAP for Google Cloud with Advanced Tools
OpenCourser.com/course/y6bqwv/managing
Managing NetApp Cloud Volumes ONTAP for Google Cloud with...
Using Ruby on Rails with Cloud SQL for PostgreSQL on Cloud Run
OpenCourser.com/course/636c93/using
Using Ruby on Rails with Cloud SQL for PostgreSQL on...
Getting Started with NetApp Cloud Manager & Cloud Volumes ONTAP for Google Cloud
OpenCourser.com/course/lihrzu/getting
Getting Started with NetApp Cloud Manager & Cloud Volumes...
Google Cloud SDK: Qwik Start - Redhat/Centos
OpenCourser.com/course/mm6fpk/google
Google Cloud SDK: Qwik Start - Redhat/Centos
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
Our mission
OpenCourser helps millions of learners each year. People visit us to learn workspace skills, ace their exams, and nurture their curiosity.
Our extensive catalog contains over 50,000 courses and twice as many books. Browse by search, by topic, or even by career interests. We'll match you to the right resources quickly.
Find this site helpful? Tell a friend about us.
Affiliate disclosure
We're supported by our community of learners. When you purchase or subscribe to courses and programs or purchase books, we may earn a commission from our partners.
Your purchases help us maintain our catalog and keep our servers humming without ads.
Thank you for supporting OpenCourser.
© 2016 - 2024 OpenCourser