Computer Vision Fundamentals with Google Cloud

Computer Vision Fundamentals with Google Cloud

8 hours Intermediate universal_currency_alt 40 Credits

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.

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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
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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.
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