This platform provides an end-to-end solution for building, deploying, and managing machine learning models. One of my favorite tools to use is Google Vertex AI. Which tool has been your favorite to use? Why? This includes features like automated model tuning, model management, and model serving.Īnother useful Google tool that I often use is Google Colab, a cloud-based notebook that enables users to run and share Jupyter notebooks with Python code, including TensorFlow code. With Vertex AI, developers can implement MLOps practices to efficiently manage, monitor, and govern their ML workloads. This powerful platform enables developers to accelerate machine learning development and deployment by providing a unified platform for data, AI, and tooling for both pre-trained and custom models.
It is employed in a variety of applications including image recognition, speech recognition, and natural language processing.īesides TensorFlow, I have used several cloud-based products for ML/AI development, such as Google's Vertex AI. I used TensorFlow, one of the most widely used tools for building machine learning models. What Google tools have you used to build? Starting today, you can build watch faces in this new format and publish them on Google Play, ready for when the first Wear OS 4 watches are available.Google Developer Expert, Machine Learning Women Techmakers Ambassador Jeddah, Saudi Arabia Data Scientist Twitter LinkedIn For example, you no longer need to update your watch face to benefit from improvements in performance or battery consumption, or to get the latest bug fixes. Watch faces that are built with this new format require less maintenance and fewer updates than the ones built using the Jetpack Watch Face library. The Wear OS platform takes care of the logic needed to render the watch face so you no longer have to worry about code optimizations or battery performance.
This means that there is no executable code involved in creating a watch face, and there will be no code embedded in your watch face APK. The Watch Face Format is a declarative XML format to design the appearance and behavior of watch faces. We are excited to announce the launch of the Watch Face Format! We worked in partnership with Samsung to introduce a new way for you to build watch faces for Wear OS smartwatches.
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