Master TensorFlow and Keras for machine learning, from data pipelines to model deployment on Google Cloud Platform.
Master TensorFlow and Keras for machine learning, from data pipelines to model deployment on Google Cloud Platform.
This course cannot be purchased separately - to access the complete learning experience, graded assignments, and earn certificates, you'll need to enroll in the full Machine Learning on Google Cloud Specialization program. You can audit this specific course for free to explore the content, which includes access to course materials and lectures. This allows you to learn at your own pace without any financial commitment.
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What you'll learn
Create TensorFlow and Keras machine learning models
Use tf.data library for large dataset manipulation
Implement neural networks with Sequential and Functional APIs
Deploy ML models at scale with Vertex AI
Optimize model performance and accuracy
Skills you'll gain
This course includes:
1.85 Hours PreRecorded video
4 quizzes
Access on Mobile, Tablet, Desktop
FullTime access
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There are 6 modules in this course
This comprehensive course covers designing and building TensorFlow input data pipelines, creating ML models with TensorFlow and Keras, and deploying them at scale with Vertex AI. Students learn to handle large datasets, implement neural networks using Sequential and Functional APIs, and optimize model performance through advanced techniques. The curriculum includes hands-on labs and practical exercises for real-world machine learning applications.
Introduction to the Course
Module 1 · 0 Minutes to complete
Introduction to the TensorFlow Ecosystem
Module 2 · 41 Minutes to complete
Design and Build an Input Data Pipeline
Module 3 · 5 Hours to complete
Building Neural Networks with the TensorFlow and Keras API
Module 4 · 4 Hours to complete
Training at Scale with Vertex AI
Module 5 · 2 Hours to complete
Summary
Module 6 · 40 Minutes to complete
Fee Structure
Instructor
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