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Google Cloud Training

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

The Cloud Vision API lets you understand the content of an image by encapsulating powerful machine learning models in a simple REST API. In this lab you’ll send an image to the Cloud Vision API and have it identify objects, faces, and landmarks.

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What's inside

Syllabus

Detect Labels, Faces, and Landmarks in Images with the Cloud Vision API

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Provides practical, hands-on experience with the Cloud Vision API
Suitable for beginners in computer vision and image analysis
Can be used to reinforce existing skills in computer vision and image analysis

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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 Detect Labels, Faces, and Landmarks in Images with the Cloud Vision API with these activities:
Review Google Cloud Fundamentals
Familiarize yourself with the fundamentals of Google Cloud and its services, as this course delves into the specific capabilities of the Cloud Vision API.
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Show steps
  • Follow the official Google Cloud Fundamentals tutorial.
  • Complete the interactive labs and exercises provided in the tutorial.
Read 'Computer Vision: Algorithms and Applications'
Read 'Computer Vision: Algorithms and Applications' to gain a deeper understanding of the theoretical foundations of computer vision.
View Computer Vision on Amazon
Show steps
  • Read the book.
  • Take notes and highlight important passages.
  • Discuss the book with other students or a mentor.
Follow a tutorial on using the Cloud Vision API
Follow a tutorial on how to use the Cloud Vision API to gain a better understanding of its features.
Browse courses on Cloud Vision API
Show steps
  • Find a tutorial on using the Cloud Vision API.
  • Follow the steps in the tutorial.
  • Experiment with the code and try different scenarios.
Seven other activities
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Join a study group for the Cloud Vision API
Join a study group for the Cloud Vision API to collaborate with other students and learn from each other.
Browse courses on Cloud Vision API
Show steps
  • Find a study group for the Cloud Vision API.
  • Attend study group meetings regularly.
  • Participate in discussions and ask questions.
Practice Image Analysis with Python
Gain hands-on experience in using the Cloud Vision API for image analysis tasks.
Browse courses on Image Analysis
Show steps
  • Set up a Python development environment with the Cloud Vision API library.
  • Develop Python scripts to perform image analysis tasks such as object detection, face detection, and landmark detection.
Practice using the Cloud Vision API
Practice using the Cloud Vision API to recognize objects, faces, and landmarks in images.
Browse courses on Cloud Vision API
Show steps
  • Create a Google Cloud Platform project and enable the Cloud Vision API.
  • Install the Google Cloud SDK.
  • Write a Python script to send an image to the Cloud Vision API.
  • Run your script and analyze the results.
Build an Image Classifier
Apply your understanding of the Cloud Vision API by building a project that classifies images into different categories.
Browse courses on Image Classification
Show steps
  • Gather a dataset of images.
  • Use the Cloud Vision API to train a machine learning model for image classification.
  • Deploy the model and evaluate its performance.
Create a presentation on the Cloud Vision API
Create a presentation on the Cloud Vision API to reinforce your understanding and share your knowledge with others.
Browse courses on Cloud Vision API
Show steps
  • Gather information about the Cloud Vision API.
  • Organize your information into a logical flow.
  • Create visual aids to illustrate your points.
  • Practice your presentation.
  • Deliver your presentation to an audience.
Contribute to an open-source project related to the Cloud Vision API
Contribute to an open-source project related to the Cloud Vision API to gain experience and give back to the community.
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Show steps
  • Find an open-source project related to the Cloud Vision API.
  • Identify an issue or feature that you can contribute to.
  • Fork the project and make your changes.
  • Submit a pull request.
Develop a mobile app using the Cloud Vision API
Develop a mobile app using the Cloud Vision API to apply your knowledge to a practical project.
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Show steps
  • Ideate and design your mobile app.
  • Develop the front-end of your app.
  • Integrate the Cloud Vision API into your app.
  • Test and deploy your app.

Career center

Learners who complete Detect Labels, Faces, and Landmarks in Images with the Cloud Vision API will develop knowledge and skills that may be useful to these careers:
Computer Vision Engineer
Computer Vision Engineers work on developing and implementing computer vision algorithms and systems. This course is a great fit for those interested in this field as it covers key concepts like using Cloud Vision API to detect labels, faces, and landmarks in images. These skills will be essential for building and maintaining computer vision systems for various applications.
Data Scientist
Data Scientists use their ability to interpret data and develop mathematical models and algorithms to solve business problems. As an emerging career that crosses several subject areas including mathematics, statistics, and computer science, this course may be a great stepping stone for those who want to pursue a career in this field. It goes over key concepts such as identifying objects, faces, and landmarks using Cloud Vision API, all of which can be useful for working with images and visual data.
Software Engineer
Software Engineers have a strong understanding of computer science fundamentals and can design, develop, and maintain software systems. This course may be helpful for those interested in the software engineering field as it covers important concepts such as using APIs and working with images and visual data. These skills are essential for building robust and efficient software applications.
Machine Learning Engineer
Machine Learning Engineers design, develop, and maintain machine learning models and systems. This course may be helpful for those interested in this field as it covers important concepts such as using APIs and working with images and visual data. These skills can be used to build and deploy machine learning models for various applications.
Data Analyst
Data Analysts clean, analyze, and interpret data to extract meaningful insights. This course may be useful for those interested in this field as it covers important concepts such as using APIs and working with images and visual data. These skills can be used to analyze and visualize data for various business applications.
Web Developer
Web Developers design, develop, and maintain websites and web applications. This course may be helpful for those interested in this field as it covers important concepts such as using APIs and working with images and visual data. These skills can be used to build and maintain websites that are visually engaging and interactive.
Graphic designer
Graphic Designers create visual concepts for various media, including print, web, and mobile. This course may be helpful for those interested in this field as it covers important concepts such as identifying objects, faces, and landmarks in images. These skills can be used to create visually appealing designs that effectively communicate messages.
Product Manager
Product Managers are responsible for defining and managing the development of products. This course may be helpful for those interested in this field as it covers important concepts such as identifying objects, faces, and landmarks in images. These skills can be used to understand user needs and develop products that meet those needs.
UX Designer
UX Designers design and evaluate user interfaces for products and services. This course may be helpful for those interested in this field as it covers important concepts such as identifying objects, faces, and landmarks in images. These skills can be used to create user interfaces that are both visually appealing and easy to use.
Photographer
Photographers capture and edit images for various purposes, including art, journalism, and advertising. This course may be helpful for those interested in this field as it covers important concepts such as identifying objects, faces, and landmarks in images. These skills can be used to capture and edit images that effectively tell stories and convey emotions.
Visual Effects Artist
Visual Effects Artists create and manipulate images and videos for film, television, and other media. This course may be helpful for those interested in this field as it covers important concepts such as identifying objects, faces, and landmarks in images. These skills can be used to create realistic and visually stunning visual effects.
Architect
Architects design and oversee the construction of buildings and other structures. This course may be helpful for those interested in this field as it covers important concepts such as identifying objects, faces, and landmarks in images. These skills can be used to design and visualize buildings and other structures.
Urban Planner
Urban Planners design and oversee the development of cities and towns. This course may be helpful for those interested in this field as it covers important concepts such as identifying objects, faces, and landmarks in images. These skills can be used to design and visualize urban areas.
Interior designer
Interior Designers design and decorate interior spaces. This course may be helpful for those interested in this field as it covers important concepts such as identifying objects, faces, and landmarks in images. These skills can be used to create visually appealing and functional interior spaces.
Landscape Architect
Landscape Architects design and oversee the construction of outdoor spaces. This course may be helpful for those interested in this field as it covers important concepts such as identifying objects, faces, and landmarks in images. These skills can be used to design and visualize outdoor spaces.

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 Detect Labels, Faces, and Landmarks in Images with the Cloud Vision API.
Provides a comprehensive overview of computer vision algorithms and applications. It covers a wide range of topics, from image formation and representation to object detection and recognition. It good choice for anyone who wants to learn more about the fundamentals of computer vision.
Classic textbook on computer vision. It provides a clear and concise introduction to the field, covering a wide range of topics from image processing to object recognition. It good choice for anyone who wants to learn the basics of computer vision.
Provides a practical introduction to deep learning for computer vision. It covers a wide range of topics, from image classification to object detection and segmentation. It good choice for anyone who wants to learn how to apply deep learning to computer vision problems.
Provides a comprehensive overview of deep learning. It covers a wide range of topics, from the basics of neural networks to the latest advances in deep learning research. It good choice for anyone who wants to learn more about the fundamentals of deep learning.
Provides a comprehensive overview of pattern recognition. It covers a wide range of topics, from statistical pattern recognition to neural networks and deep learning. It good choice for anyone who wants to learn more about the fundamentals of pattern recognition.
Provides a comprehensive overview of machine learning from a probabilistic perspective. It covers a wide range of topics, from supervised learning to unsupervised learning and reinforcement learning. It good choice for anyone who wants to learn more about the fundamentals of machine learning from a theoretical perspective.
Provides a comprehensive overview of digital image processing. It covers a wide range of topics, from image formation to image enhancement and analysis. It good choice for anyone who wants to learn more about the fundamentals of digital image processing.
Provides a practical introduction to deep learning using Python. It covers a wide range of topics, from getting started with Python to building and training deep learning models. It good choice for anyone who wants to learn how to use Python for deep learning.
Provides a comprehensive overview of pattern recognition and machine learning. It covers a wide range of topics, from statistical learning to neural networks and deep learning. It good choice for anyone who wants to learn more about the fundamentals of pattern recognition and machine learning.
Provides a friendly and accessible introduction to machine learning. It covers a wide range of topics, from supervised learning to unsupervised learning and reinforcement learning. It good choice for anyone who wants to learn more about the basics of machine learning without getting too technical.

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