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Computer Vision Fundamentals with Google Cloud

Computer Vision Fundamentals with Google Cloud

magic_button Data Analysis Machine Learning Deep Learning
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8 hours Intermediate

This course describes different types of computer vision use cases and then highlights different machine learning strategies for solving these use cases. The strategies vary from experimenting with pre-built ML models through pre-built ML APIs and AutoML Vision to building custom image classifiers using linear models, deep neural network (DNN) models or convolutional neural network (CNN) models.

The course shows how to improve a model's accuracy with augmentation, feature extraction, and fine-tuning hyperparameters while trying to avoid overfitting the data.

The course also looks at practical issues that arise, for example, when one doesn't have enough data and how to incorporate the latest research findings into different models.

Learners will get hands-on practice building and optimizing their own image classification models on a variety of public datasets in the labs they will work on.

Skill badges validate your practical knowledge on specific products through hands-on labs and challenge assessments. Earn a badge by completing a course or jump straight into the challenge lab to get your badge today. Badges prove your proficiency, enhance your professional profile, and ultimately lead to increased career opportunities. Visit your profile to track badges you’ve earned.

info
Course Info
Objectives
  • Understand at a high-level the types of problems computer vision may solve
  • Understand some of the key concepts and model architectures typically used using computer vision
Prerequisites
Working proficiency with Python on topics covered in the Google Crash Course on Python. Prior experience with foundational machine learning concepts and building machine learning solutions on Google Cloud as covered in Machine Learning with TensorFlow on Google Cloud.
Audience
Customers, Partners, Googlers This offering is for professional Data Scientists and ML Engineers looking to build
Available languages
English
What do I do when I finish this course?
After finishing this course, you can explore additional content in your learning path or browse the catalog.
What badges can I earn?
Upon finishing the required items in a course, you will earn a badge of completion. Badges can be viewed on your profile and shared with your social network.
Interested in taking this course with one of our authorized on-demand partners?
Explore Google Cloud content on Coursera and Pluralsight.
Prefer learning with an instructor?
View the public classroom schedule here.
Can I take this course for free?
When you enroll into most courses, you will be able to consume course materials like videos and documents for free. If a course consists of labs, you will need to purchase an individual subscription or credits to be able consume the labs. Labs can also be unlocked by any campaigns you participate in. All required activities in a course must be completed to be awarded the completion badge.

The Power of Challenge Labs

Now you can fast track your way to a skill badge without having to take the entire course. If you're confident with your skills, jump straight to the challenge lab.

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