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Ikechukwu Nigel Ogbuchi
In this 1-hour long project-based course, you will learn how to build your own Face Mask Detector model using Teachable Machine, test the trained model and export or save it for future use. Teachable Machine is a fun way of getting started with machine learning even if you do not have coding experience. Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.
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Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Develops skills and knowledge in machine learning via Teachable Machine, which are core skills for beginners in machine learning
Course is ideal for beginners as it introduces machine learning and does not require coding experience
Might not be appropriate for learners outside of North America due to regional restrictions

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Reviews summary

Google's teachable machine course

This course uses Google's Teachable Machine to teach students about machine learning. It is a project-based course that is best suited for learners in the North America region.
Introduces you to Google Teachable Machine.
"Introduces you to the Google Teachable Machine"

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 Build a Face Mask Detector with Google's Teachable Machine with these activities:
Review basic programming concepts
Refreshing programming skills will provide a stronger foundation for building the model.
Browse courses on Programming Concepts
Show steps
  • Review variables, data types, and operators
  • Practice writing simple programs
Read 'Machine Learning for Beginners' by Jake VanderPlas
This book provides a comprehensive overview of machine learning concepts.
Show steps
  • Read the book and take notes
  • Apply the concepts to the course project
Work through the Teachable Machine tutorial
Following the official tutorial will help build a strong foundation for building the model.
Show steps
  • Review the concepts of machine learning
  • Set up Teachable Machine
  • Follow the steps in the tutorial
Three other activities
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Show all six activities
Form a study group with other learners
Collaboration will enhance understanding and provide support.
Show steps
  • Find other learners who are interested in forming a study group
  • Set up a regular meeting time and place
  • Discuss the course material and work on projects together
Build multiple models with different datasets
Experimenting with different datasets will enhance understanding of how models generalize.
Browse courses on Machine Learning Models
Show steps
  • Gather different datasets related to face masks
  • Build multiple models using the different datasets
  • Compare the accuracy and performance of each model
Mentor a beginner in machine learning
Teaching others will solidify understanding and identify areas for improvement.
Browse courses on Mentoring
Show steps
  • Find a beginner who is interested in learning about machine learning
  • Set up a regular meeting time and place
  • Teach the basics of machine learning and work on projects together

Career center

Learners who complete Build a Face Mask Detector with Google's Teachable Machine will develop knowledge and skills that may be useful to these careers:
Machine Learning Engineer
Machine Learning Engineers collaborate with Data Scientists to build, deploy, and maintain machine learning models. They are responsible for designing and optimizing machine learning systems, as well as monitoring and evaluating their performance. This course provides hands-on experience with building a machine learning model, which is valuable for those interested in a career as a Machine Learning Engineer.
Data Analyst
Data Analysts collect, clean, and analyze data to provide insights to businesses. This course can help Data Analysts develop the skills needed to use machine learning techniques to analyze data and extract meaningful information.
Data Scientist
A Data Scientist creates machine learning models that power a variety of modern applications. They design, develop, and maintain algorithms to collect, clean, analyze, and interpret data. This course offers an accessible introduction to machine learning that can help individuals begin developing the skills needed for this role.
Business Analyst
Business Analysts help businesses understand their data and make informed decisions. This course can help Business Analysts develop the skills needed to use machine learning techniques to analyze data and provide insights to businesses.
Product Manager
Product Managers are responsible for the development and management of software products. This course may be helpful for Product Managers who want to gain a basic understanding of machine learning and how it can be used to improve products.
Compliance Officer
Compliance Officers are responsible for ensuring that a business complies with all applicable laws and regulations. This course may be helpful for Compliance Officers who want to learn about how machine learning can be used to automate and improve the compliance process.
Sales Manager
Sales Managers are responsible for leading and motivating sales teams. This course may be helpful for Sales Managers who want to learn about how machine learning can be used to identify and target potential customers.
Software Engineer
Software Engineers design, develop, and maintain software systems. This course provides a foundation in machine learning that can be helpful for Software Engineers who want to build and integrate machine learning capabilities into their software applications.
Financial Analyst
Financial Analysts are responsible for analyzing financial data and providing recommendations to businesses. This course may be helpful for Financial Analysts who want to learn about how machine learning can be used to automate and improve the financial analysis process.
Risk Manager
Risk Managers are responsible for identifying and mitigating risks to a business. This course may be helpful for Risk Managers who want to learn about how machine learning can be used to identify and assess risks.
Customer Success Manager
Customer Success Managers are responsible for ensuring that customers are satisfied with a company's products and services. This course may be helpful for Customer Success Managers who want to learn about how machine learning can be used to identify and resolve customer issues.
Marketing Manager
Marketing Managers are responsible for developing and executing marketing campaigns. This course may be helpful for Marketing Managers who want to learn about how machine learning can be used to target and personalize marketing campaigns.
Operations Manager
Operations Managers are responsible for planning and executing the day-to-day operations of a business. This course may be helpful for Operations Managers who want to learn about how machine learning can be used to improve efficiency and productivity.
UX Designer
UX Designers design and evaluate user interfaces. This course may be helpful for UX Designers who want to learn about how machine learning can be used to improve the user experience.
Recruiter
Recruiters are responsible for finding and hiring qualified candidates for open positions. This course may be helpful for Recruiters who want to learn about how machine learning can be used to automate and improve the recruiting process.

Reading list

We've selected six 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 Build a Face Mask Detector with Google's Teachable Machine.
Machine Learning subfield of artificial intelligence concerned with the design and development of algorithms that can learn from and make predictions on data. Teaches fundamentals of Machine Learning and deep dive into essential ML concepts, techniques and applications.
Deep Learning subfield of machine learning concerned with algorithms inspired by the structure and function of the brain called artificial neural networks. provides an introduction to the field of deep learning.
Computer Vision is an interdisciplinary scientific field that deals with how computers can gain high-level understanding from digital images or videos.
Machine learning set of algorithms that can be used to predict future events based on past data. provides a probabilistic perspective on machine learning.
Face detection and recognition subfield of computer vision that deals with the task of detecting and recognizing human faces in images and videos.

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