Google Cloud Machine Learning with TensorFlow

Google Cloud Machine Learning with TensorFlow

TensorFlow has become the first choice for deep learning tasks because of the way it facilitates building powerful and sophisticated neural networks. The Google Cloud Platform is a great place to run TF models at scale, and perform distributed training and prediction.

This course shows you how to use Google Cloud to train TensorFlow models and use them to predict results for multiple users. You will learn to efficiently train neural networks using large datasets and to serve your training models.

With this video course, you will use the power of Google's Cloud Platform to train deep neural networks faster. This course supplies various examples of training in Google Cloud AI Platform. You will also learn to run predictions for your model using the cloud. You will explore topics such as cloud infrastructures, distributed training, serverless technologies, model serving, and more.

By the end of the course, you will be expert at training and serving neural models, and beyond.

About the Author

Tobias Zwingmann is Senior Data Scientist at Deutsche Messe AG and possesses a high entrepreneurial bias. In his work, he utilizes small and big data to create value—for example, by turning analytical insights into better customer experience and higher customer engagement. He also supports the development of new data-driven businesses and prototypes new data products for his organization. He likes to learn from and meet open-minded people.

Train and predict your models using the Google Cloud ML Engine

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What you will learn

• Get access to powerful computers with GPUs organized in clusters to optimize your performance
• Train bigger models faster using the Google Cloud infrastructure
• Explore machine types and learn how to configure clusters to solve problems

Rating: 4.45

Level: Beginner Level

Duration: 4 hours

Instructor: Packt Publishing