Intro to ML: Image Processing
Introductory 5 passaggi 5 ore 25 crediti
Using large scale computing power to recognize patterns and "read" images is one of the foundational technologies in AI, from self-driving cars to facial recognition. The Google Cloud Platform provides world class speed and accuracy via systems that can utilized by simply calling APIs. With these and a host of other APIs, GCP has a tool for just about any machine learning job. In this introductory quest, you will get hands-on practice with machine learning as it applies to image processing by taking labs that will enable you to label images, detect faces and landmarks, as well as extract, analyze, and translate text from within images.
In questo lab imparerai ad addestrare un modello TensorFlow e ad eseguirne il deployment su AI Platform per l'elaborazione di previsioni. Guarda questi brevi video: Harness the Power of Machine Learning with AI Platform e AI Platform: Qwik Start - Qwiklabs Preview.
In this lab you'll upload an image to Cloud Storage then make a request to the Vision API with APIs Explorer.
AutoML Vision consente agli sviluppatori con un'esperienza limitata nell'ambito del machine learning di addestrare modelli di qualità elevata per il riconoscimento delle immagini. In questo lab pratico imparerai ad addestrare un modello personalizzato per riconoscere i diversi tipi di nuvola (cumulo, cumulonembo e così via).
The Cloud Vision API lets you understand the content of an image by encapsulating powerful machine learning models in a simple REST API. In this lab you’ll send an image to the Cloud Vision API and have it identify objects, faces, and landmarks.
In this lab you’ll combine the Cloud Vision, Natural Language, and Translation APIs to capture text strings from images, recognize characters, and analyze and translate the text strings into other languages.