Training Tensorflow Models on GCP

GCP

Google Cloud Platform (GCP) is a cloud computing platform that provides a wide range of services such as computing power, storage, and databases to businesses and individuals. GCP is known for its scalability, reliability, and security. It offers a pay-as-you-go pricing model which allows users to only pay for the services they use. GCP is used by many companies such as Spotify, Coca-Cola, and HSBC.

Tensorflow Models

TensorFlow is a free and open-source software library for machine learning and artificial intelligence. It can be used across a range of tasks but has a particular focus on training and inference of deep neural networks. TensorFlow helped launch the deep learning revolution: with pre-trained models, data, and high-level APIs, it has become easy for everyone to build ML and DL models. One of the important Tensorflow features is that it is flexible in its operating model, meaning it has modularity and the parts of it that you want to make standalone it offers you that option. TensorFlow.js is a JavaScript-based framework to run machine learning models within the browser. Any modern browser can run the TensorFlow model with no changes to the code.
GCP is a popular cloud option for companies looking to deploy Tensorflow models at scale. Kaspian securely deploys into your GCP environment, ensuring that all storage and compute assets remain within your cloud. Kaspian's flexible compute layer empowers data teams to train Tensorflow models on GCP in a highly performant, scalable, and configurable manner, with native support for autoscaling, GPU acceleration, and more.
Learn more about Kaspian and see how our flexible compute layer for the modern data cloud is already reshaping the way companies in industries like retail, manufacturing and logistics are thinking about data engineering and analytics.

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