Comprehensive platform for data science and machine learning
Google AI Platform makes it easy for developers, scientists, and data engineers to optimize their machine learning workflows. With AI Platform, all users can smoothly move their projects from conception to deployment, whether it's optimizing advanced models or performing data science tasks through AutoML. Take advantage of Google's expertise in the artificial intelligence industry by integrating our revolutionary AI technologies into your applications using tools like TPUs and TensorFlow.


Prepare
Prepare and store data sets with BigQuery. Then tag your training data with the help of the built-in Data Tagging Service. To do this, it applies functions such as classification, object detection and entity extraction to images, videos, audios and texts.
To create
AutoML and its simple interface allow you to create the best machine learning (Machine Learning) models without having to write a single line of code. You can also create them using your own code in AI Platform Notebooks, a managed Jupyter Notebook service that offers fully configured environments for developing models. Once created, AI Platform Training allows you to train them in the cloud.


Validate
Validate your models with AI Explanations, a tool that helps you interpret the results they generate, verify their behavior and detect biases. In addition, it offers you ideas to improve your models and your training data. If you want to go a step further, use AI Platform Vizier, a black box optimization service with which you can adjust hyperparameters and refine the results of your models.
To deploy
Deploy your models at scale and get predictions in the cloud with Google's AI Platform Prediction, which manages the infrastructure needed to run your models and makes it easy to access to make prediction requests online and in batches. You can also use AutoML Vision Edge to deploy your models at the edge and generate real-time actions based on local data. For its part, TensorFlow Enterprise provides enterprise-grade support for your TensorFlow instance.


Machine learning operations
Manage your models, experiments, and end-to-end workflows through machine learning operations. To do this, AI Platform Pipelines allows you to deploy consolidated and repeatable processing flows. In addition, thanks to continuous evaluation, you can monitor the performance of your models over time and receive feedback on it on an ongoing basis.
Integral Life Cycle of Automatic Learning (Machine Learning)

Development with AI
We offer solutions that enable developers, scientists, and data engineers to quickly and cost-effectively deploy their projects.


Conventional AI
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