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End-to-End Machine Learning with TensorFlow on Google Cloud

This course is set up as a workshop where you will do End-to-End Machine Learning with TensorFlow on Google Cloud Platform. It involves building an end-to-end model from data exploration all the way to deploying an ML model and getting predictions from it.

One of the best ways to review something is to work with the concepts and technologies that you have learned. So, this course is set up as a workshop and in this workshop, you will do End-to-End Machine Learning with TensorFlow on Google Cloud Platform. It involves building an end-to-end model from data exploration all the way to deploying an ML model and getting predictions from it.

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What's inside

Syllabus

Welcome to the Course

Machine Learning (ML) on Google Cloud Platform (GCP)

Explore the Data

Create the dataset

Build the Model

Operationalize the model

Summary

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

This course is highly relevant for learners interested in undertaking hands-on ML projects on Google Cloud Platform using Tensorflow

Provides an overview of the ML lifecycle, from data exploration to model deployment

Real-world use cases, interactive exercises, and practical labs

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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 End-to-End Machine Learning with TensorFlow on Google Cloud with these activities:

Read 'Hands-On Machine Learning with TensorFlow 2'

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Thorough coverage of TensorFlow and ML concepts.

View Hands-On Machine Learning with Scikit-Learn,... on Amazon

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Purchase or borrow the book.
Read the book thoroughly, taking notes and highlighting important concepts.
Complete the exercises and projects provided in the book.

Brush-up on Linear Algebra concepts

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Refresh your understanding of linear algebra to enhance your ability to manipulate and analyze mathematical expressions.

Browse courses on Linear Algebra

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Review matrix operations like addition, multiplication, and inversion.
Explore concepts of vector spaces, subspaces, and their properties.
Practice solving systems of linear equations using techniques such as Gaussian elimination.

Compile ML Resources

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Organization of resources enhances accessibility and retention.

Browse courses on TensorFlow

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Gather online resources, tutorials, and documentation related to TensorFlow and ML on GCP.
Organize these resources into a structured format, such as a Notion page or a Google Doc.
Categorize the resources based on topics or difficulty levels.
Review and update your compilation regularly to ensure its relevance.

Five other activities

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Explore TensorFlow Tutorials

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Familiarize yourself with TensorFlow and its features through official tutorials.

Browse courses on TensorFlow

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Visit the TensorFlow website and explore various tutorials.
Select a beginner-friendly tutorial and study it thoroughly.
Follow the step-by-step instructions and complete the tutorial.

Attend a TensorFlow Workshop

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In-person workshops offer hands-on experience and networking opportunities.

Browse courses on TensorFlow

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Research and identify relevant TensorFlow workshops.
Register for a workshop that aligns with your skill level.
Attend the workshop and actively participate in the activities.
Engage with instructors and other participants to exchange knowledge.

Mentor Junior ML Enthusiasts

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Sharing knowledge reinforces understanding and fosters community.

Browse courses on TensorFlow

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Identify platforms or forums where you can connect with junior ML enthusiasts.
Offer your support and guidance to those who need assistance.
Answer questions, provide resources, and share your experiences.
Foster a positive and supportive learning environment.

Build a Mini ML Project

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Practical application of TensorFlow and GCP in a personal project.

Browse courses on TensorFlow

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Identify a small-scale ML problem that you're interested in.
Gather or create a dataset for your project.
Develop a TensorFlow model and train it using your dataset.
Deploy your model and obtain predictions.

Volunteer in AI/ML Projects

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Real-world experience in AI/ML contributes to deeper understanding.

Browse courses on TensorFlow

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Research and identify organizations or projects involved in AI/ML.
Contact the organizations and express your interest in volunteering.
Contribute your skills to specific tasks or projects within the organization.
Seek feedback from experienced professionals and learn from their expertise.

Career center

Learners who complete End-to-End Machine Learning with TensorFlow on Google Cloud will develop knowledge and skills that may be useful to these careers:

Machine Learning Engineer

Machine Learning Engineers work to design, develop, and maintain machine learning systems. This course provides a great opportunity to build a foundational understanding of the end-to-end machine learning lifecycle. The course uses Google Cloud Platform and TensorFlow, which are industry-leading tools for deploying and building machine learning models.

See salaries and explore the career path for Machine Learning Engineer

Data Analyst

Data Analysts collect, clean, and analyze data to provide insights and recommendations. This course provides a great foundation for Data Analysts interested in learning more about machine learning. The course uses Google Cloud Platform and TensorFlow, which are industry-leading tools for deploying and building machine learning models.

See salaries and explore the career path for Data Analyst

Quantitative Analyst

Quantitative Analysts use mathematical and statistical models to analyze data and make predictions. This course provides an excellent foundation in machine learning, which can be helpful for Quantitative Analysts looking to expand their skillset and stay ahead of the curve.

See salaries and explore the career path for Quantitative Analyst

Data Scientist

Data Scientists gather, analyze, interpret, and present complex data in order to find trends and patterns. This course is a helpful starting point for Data Scientists because it provides an opportunity to build an end-to-end machine learning model using Google Cloud Platform. Familiarizing the learner with TensorFlow, this course helps teach how to build models to make predictions and solve real-world problems using machine learning.

See salaries and explore the career path for Data Scientist

Software Engineer

Software Engineers design, develop, and maintain software systems. This course provides an excellent introduction to the rapidly-growing field of machine learning. It may be especially helpful to Software Engineers interested in using Google Cloud Platform and TensorFlow to develop machine learning applications.

See salaries and explore the career path for Software Engineer

Market Research Analyst

Market Research Analysts collect and analyze data to understand market trends and consumer behavior. This course provides a great foundation in end-to-end machine learning, which can be helpful for Market Research Analysts looking to expand their skillset and stay ahead of the curve.

See salaries and explore the career path for Market Research Analyst

Business Analyst

Business Analysts help organizations make better decisions by analyzing data and trends. This course provides a foundation in end-to-end machine learning, which can be helpful for Business Analysts looking to expand their skillset and stay ahead of the curve.

See salaries and explore the career path for Business Analyst

Statistician

Statisticians collect, analyze, and interpret data to provide insights and recommendations. This course provides a foundation in end-to-end machine learning, which can be helpful for Statisticians looking to expand their skillset and stay ahead of the curve.

See salaries and explore the career path for Statistician

Risk Analyst

Risk Analysts assess and manage risk for organizations. This course provides a foundation in end-to-end machine learning, which can be helpful for Risk Analysts looking to build and deploy machine learning models to identify and mitigate risks.

See salaries and explore the career path for Risk Analyst

Product Manager

Product Managers are responsible for the development and launch of new products and features. This course provides a solid foundation in machine learning, which can be helpful for Product Managers looking to build innovative products and features that leverage machine learning.

See salaries and explore the career path for Product Manager

Consultant

Consultants provide advice and guidance to organizations on a variety of topics. This course provides a solid foundation in machine learning, which can be helpful for Consultants looking to expand their skillset and stay ahead of the curve. Particularly helpful for those in Data Science or Technology Consulting.

See salaries and explore the career path for Consultant

Data Engineer

Data Engineers design, build, and maintain data systems. This course provides a solid foundation in machine learning, which can be helpful for Data Engineers looking to build and deploy machine learning models to analyze and process data.

See salaries and explore the career path for Data Engineer

Financial Analyst

Financial Analysts use data and analysis to make recommendations about investments and financial decisions. This course provides a solid foundation in machine learning, which can be helpful for Financial Analysts looking to build and deploy machine learning models to analyze financial data.

See salaries and explore the career path for Financial Analyst

Operations Research Analyst

Operations Research Analysts use mathematical and analytical techniques to solve complex business problems. This course provides a solid foundation in machine learning, which can be helpful for Operations Research Analysts looking to build and deploy machine learning models to solve business problems.

See salaries and explore the career path for Operations Research Analyst

Technical Writer

Technical Writers create and maintain documentation for technical products and services. This course provides a solid foundation in machine learning, which can be helpful for Technical Writers looking to document and explain machine learning concepts and applications.

See salaries and explore the career path for Technical Writer

Reading list

We've selected 11 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 End-to-End Machine Learning with TensorFlow on Google Cloud.

Deep Learning for the Life Sciences

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Good supplement for anyone learning Tensorflow for Deep Learning. It provides a practical introduction to TensorFlow for building deep learning models.

End-to-End Machine Learning with TensorFlow on Google Cloud

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What's inside

Syllabus

Good to know

Save this course

Activities

Career center

Reading list

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