Developing Data and Machine Learning Apps with C#
Advanced 9 étapes 8 heures 45 crédits
C# has powered Windows .NET application development for nearly two decades and Google Cloud is committed to supporting developers getting their .NET workloads up and running on the GCP platform. In this quest, you will learn how to run C# apps in GCP, and specifically how to take your apps to the next level by interfacing them with the big data and machine learning APIs that are accessible now from C#. By enrolling in Developing Data and Machine Learning Apps with C# you will see firsthand how seamlessly GCP integrates with .NET workloads and what the possibilities are for leveraging big data and ML services in your own C# projects.
Prérequis :As this Quest relies heavily on the C# programming language, the student should be an experienced programmer with C#. It is also recommended that the student have at least earned a Badge by completing the Baseline: Data, ML, AI and possibly those in the Machine Learning APIs Quests before beginning.
Dans cet atelier, vous allez découvrir l'architecture et le fonctionnement de base d'une API (Application Programming Interface, interface de programmation d'application). Cet atelier sera complété par des exercices pratiques, au cours desquels vous serez amené à configurer et exécuter des méthodes d'API Cloud Storage dans Cloud Shell.
In this lab you will use Google Cloud Client Libraries for .NET to query BigQuery public datasets with C#.
In this lab you will learn how to perform sentiment, entity, and syntax analysis with the Natural Language API.
In this lab you'll learn how to send an audio file in English and other languages to the Cloud Speech-to-Text API for transcription.
In this lab you'll learn how to list available voices and also synthesize audio from text using the Text-to-Speech API.
In this lab you'll learn how to use BigQuery with C#
In this lab you'll learn how to perform text detection, landmark detection, and face detection with the Vision API.
In this lab you will learn how to list available languages, translate text and also detect language of a given text.
In this hands-on lab you learn how to create a gaming leaderboard using a Cloud Spanner database table with a commit timestamp column.