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Google Cloud Training
This is a self-paced lab that takes place in the Google Cloud console. In this lab, you learn the basic ‘Hello World' of machine learning. Instead of programming explicit rules in a language such as Java or C++, you build a system that is trained on data to infer the rules that determine a relationship between numbers.
Register for this course and see more details by visiting:
OpenCourser.com/course/3ppgn5/learning
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What's inside
Syllabus
Learning TensorFlow: the Hello World of Machine Learning
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Builds a strong foundation for beginners by introducing basic concepts of machine learning using TensorFlow
Hands-on labs and interactive materials enhance the learning experience
Instructors from Google Cloud Training, recognized for their expertise in machine learning
Introduces TensorFlow, a widely adopted machine learning framework in industry
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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 Learning TensorFlow: the Hello World of Machine Learning with these
activities:
Deep Learning with Python
Show steps
Gain a deeper understanding of deep learning concepts and techniques by reading a comprehensive book on the subject.
View
Deep Learning with Python, Second Edition
on Amazon
Show steps
-
Purchase or borrow the book
-
Read the book thoroughly
-
Take notes and highlight important concepts
-
Complete the exercises and assignments
TensorFlow Tutorial
Show steps
Get a solid foundation in the basics of TensorFlow, the open-source machine learning library.
Browse courses on
TensorFlow
Show steps
-
Visit the TensorFlow website
-
Follow the step-by-step tutorial
-
Complete the exercises
Machine Learning Study Group
Show steps
Enhance your understanding by discussing concepts, sharing resources, and working on problems with fellow learners.
Browse courses on
Machine Learning
Show steps
-
Find or start a study group with other students
-
Establish regular meeting times
-
Prepare for each session by reviewing materials
-
Actively participate in discussions and problem-solving
Three other activities
Expand to see all activities and additional details
Show all six activities
Machine Learning Workshop
Show steps
Expand your knowledge and skills by attending a workshop where you can learn from experts and work on practical projects.
Browse courses on
Machine Learning
Show steps
-
Find a reputable machine learning workshop
-
Register for the workshop
-
Attend the workshop and actively participate
-
Complete the workshop assignments and exercises
Machine Learning Code Challenges
Show steps
Sharpen your machine learning coding skills by solving a series of challenging coding problems.
Browse courses on
Machine Learning
Show steps
-
Find a reputable online coding challenge platform
-
Choose a challenge that aligns with your skill level
-
Attempt to solve the challenge on your own
-
Review the solution and identify areas for improvement
Contribute to TensorFlow Ecosystem
Show steps
Solidify your understanding and make a meaningful contribution to the machine learning community by contributing to TensorFlow's open-source ecosystem.
Browse courses on
TensorFlow
Show steps
-
Identify an area where you can contribute
-
Fork the TensorFlow repository
-
Make changes and test your contribution
-
Submit a pull request
Deep Learning with Python
Show steps
Gain a deeper understanding of deep learning concepts and techniques by reading a comprehensive book on the subject.
View
Deep Learning with Python, Second Edition
on Amazon
Show steps
Show steps
Show steps
- Purchase or borrow the book
- Read the book thoroughly
- Take notes and highlight important concepts
- Complete the exercises and assignments
TensorFlow Tutorial
Show steps
Get a solid foundation in the basics of TensorFlow, the open-source machine learning library.
Browse courses on
TensorFlow
Show steps
Show steps
Show steps
- Visit the TensorFlow website
- Follow the step-by-step tutorial
- Complete the exercises
Machine Learning Study Group
Show steps
Enhance your understanding by discussing concepts, sharing resources, and working on problems with fellow learners.
Browse courses on
Machine Learning
Show steps
Show steps
Show steps
- Find or start a study group with other students
- Establish regular meeting times
- Prepare for each session by reviewing materials
- Actively participate in discussions and problem-solving
Three other activities
Expand to see all activities and additional details
Show all six activities
Machine Learning Workshop
Show steps
Expand your knowledge and skills by attending a workshop where you can learn from experts and work on practical projects.
Browse courses on
Machine Learning
Show steps
Show steps
Show steps
- Find a reputable machine learning workshop
- Register for the workshop
- Attend the workshop and actively participate
- Complete the workshop assignments and exercises
Machine Learning Code Challenges
Show steps
Sharpen your machine learning coding skills by solving a series of challenging coding problems.
Browse courses on
Machine Learning
Show steps
Show steps
Show steps
- Find a reputable online coding challenge platform
- Choose a challenge that aligns with your skill level
- Attempt to solve the challenge on your own
- Review the solution and identify areas for improvement
Contribute to TensorFlow Ecosystem
Show steps
Solidify your understanding and make a meaningful contribution to the machine learning community by contributing to TensorFlow's open-source ecosystem.
Browse courses on
TensorFlow
Show steps
Show steps
Show steps
- Identify an area where you can contribute
- Fork the TensorFlow repository
- Make changes and test your contribution
- Submit a pull request
Career center
Learners who complete Learning TensorFlow: the Hello World of Machine Learning will develop knowledge and skills
that may be useful to these careers:
Data Scientist
Data Scientist
A Data Scientist analyzes and interprets large amounts of data to find patterns and trends. They use their findings to make predictions and recommendations that can help businesses make better decisions. This course may be useful for those wanting to transition into the field or expand their current skillset.
Machine Learning Engineer
Machine Learning Engineer
A Machine Learning Engineer designs, develops, and implements machine learning systems within complex hardware systems. The engineer uses their skills to create algorithms that can make accurate predictions based on data. This course may be useful for those wanting to transition into the field or expand their current skillset.
Statistician
Statistician
A Statistician collects, analyzes, and interprets data to help businesses and organizations make informed decisions. This course may be useful for those wanting to transition into the field or expand their current skillset.
Actuary
Actuary
An Actuary uses mathematical and statistical models to assess and manage risk. This course may be useful for those wanting to transition into the field or expand their current skillset.
Software Engineer
Software Engineer
Building and maintaining machine learning systems requires strong programming and software engineering skills. This course helps provide a foundation in these concepts, making it a useful addition to any beginner software engineer's skillset.
Quantitative Analyst
Quantitative Analyst
A Quantitative Analyst uses mathematical and statistical models to analyze financial data and make investment recommendations. This course may be useful for those wanting to transition into the field or expand their current skillset.
Operations Research Analyst
Operations Research Analyst
An Operations Research Analyst uses mathematical and analytical techniques to improve the efficiency and effectiveness of systems. This course may be useful for those wanting to transition into the field or expand their current skillset.
Project Manager
Project Manager
A Project Manager plans and executes projects. This course may be useful for those wanting to transition into the field or expand their current skillset.
Market Researcher
Market Researcher
A Market Researcher studies market trends and consumer behavior to help businesses make informed decisions. This course may be useful for those wanting to transition into the field or expand their current skillset.
Business Analyst
Business Analyst
A Business Analyst uses data and analysis to solve business problems. This course may be useful for those wanting to transition into the field or expand their current skillset.
Data Analyst
Data Analyst
A Data Analyst analyzes and interprets large amounts of data to find patterns and trends. They use their findings to make recommendations that can help businesses make better decisions. This course may be useful for those wanting to transition into the field or expand their current skillset.
Financial Analyst
Financial Analyst
A Financial Analyst uses financial data and analysis to make investment recommendations. This course may be useful for those wanting to transition into the field or expand their current skillset.
Risk Analyst
Risk Analyst
A Risk Analyst analyzes and manages risk. This course may be useful for those wanting to transition into the field or expand their current skillset.
Product Manager
Product Manager
A Product Manager is responsible for the development and marketing of a product. This course may be useful for those wanting to transition into the field or expand their current skillset.
Business Intelligence Analyst
Business Intelligence Analyst
A Business Intelligence Analyst uses data and analysis to improve the efficiency and effectiveness of business processes. This course may be useful for those wanting to transition into the field or expand their current skillset.
For more career information including salaries, visit:
OpenCourser.com/course/3ppgn5/learning
Reading list
We've selected eight 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
Learning TensorFlow: the Hello World of Machine Learning.
Save
This textbook provides a comprehensive overview of deep learning, including foundational concepts, algorithms, and applications.
Provides hands-on examples and code snippets to implement machine learning algorithms using popular libraries like Scikit-Learn, Keras, and TensorFlow.
This textbook provides a comprehensive and practical introduction to deep learning with Python, covering topics such as neural networks, image recognition, and natural language processing.
Provides a comprehensive guide to machine learning with Python, covering topics such as data manipulation, feature engineering, and model selection.
Provides a comprehensive guide to machine learning with R, covering topics such as data preprocessing, model building, and evaluation.
Provides a simplified and accessible introduction to machine learning for beginners.
Provides a very basic introduction to machine learning for complete beginners.
Save
Provides a theoretical foundation for machine learning, covering topics such as linear algebra, optimization, and statistical inference.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/3ppgn5/learning
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Via
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Institution
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Instructor
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Language
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Good to know
Builds a strong foundation for beginners by introducing basic concepts of machine learning using TensorFlow
Hands-on labs and interactive materials enhance the learning experience
Instructors from Google Cloud Training, recognized for their expertise in machine learning
Introduces TensorFlow, a widely adopted machine learning framework in industry
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