This course covers designing and building a TensorFlow input data pipeline, building ML models with TensorFlow and Keras, improving the accuracy of ML models, writing ML models for scaled use, and writing specialized ML models.
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About this Course
Could your company benefit from training employees on in-demand skills?
Try Coursera for BusinessWhat you will learn
Create TensorFlow and Keras machine learning models and understand their key components
Use the tf.data library to manipulate data and large datasets
Use the Keras Sequential and Functional APIs for simple and advanced model creation
Train, deploy, and productionalize ML models at scale with Vertex AI
Skills you will gain
- Machine Learning
- Python Programming
- Build Input Data Pipeline
- Tensorflow
- keras
Could your company benefit from training employees on in-demand skills?
Try Coursera for BusinessOffered by
Syllabus - What you will learn from this course
Introduction to the Course
Introduction to the TensorFlow ecosystem
Design and Build an Input Data Pipeline
Building Neural Networks with the TensorFlow and Keras API
Training at Scale with Vertex AI
Summary
Reviews
- 5 stars61.90%
- 4 stars25.10%
- 3 stars8.93%
- 2 stars2.54%
- 1 star1.51%
TOP REVIEWS FROM TENSORFLOW ON GOOGLE CLOUD
Excellent 'Introduction' to TensorFlow 2.0 (HINT: 'Introduction' does not mean 'Easy').
Evan Jones is at his best giving rapid intuitive explanations of advanced topics in deep neural networks.
Nice start. Have a look at Andrew NG's course, especially how they do the labs. Might give you some ideas for your next class versions.
I feel this course very valuable because it taught how to create an automated service in cloud with very huge data and working with distributed systems in production environment with minimal time.
Nice introduce, might be more on introduce the model structure, because I still need to read additional notes to locate how to train my deep learning model online.
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