Pre-trained APIs

1. Pre-trained APIs

Google Cloud's pre trained API's are a great option If you don't have your own training data. These are ideal in situations where an organization doesn't have specialized data scientists, but it does have business analysts and developers. This is the fastest and lowest effort of the machine learning approaches, but is less customizable than the others. Google Cloud's pre trained API's can help developers build smart apps quickly by providing access to ML models for common tasks like analyzing images, videos, and text. API's can be deployed in a virtual private cloud, on premises, or in Google's public cloud regardless of the level of ML experience. Let's imagine a developer building a mobile app that users will submit photos to the developer needs the app to recognize what the images are and filter out any that aren't safe for work. The developer might choose Vision API. This offers powerful, pre trained machine learning models, which use Google data to automatically detect faces, objects, text, and even sentiment in images. The developer can use Vision API to assign labels to images and quickly classify them into millions of predefined categories. The natural language API is another out of the box, pre trained API. If a business has a contact form on its website that receives many messages every day. This data can be difficult and time intensive to manually handle, categorize an action. Natural language API discovers syntax, entities and sentiment in text and classifies texts into a predefined set of categories. In this case, it can decide if comments represent complaints, Praise, and attempt to learn more about your business and more. Google also offers several other pre trained API's. The Cloud Translation API converts texts from one language to another. The speech to text API converts audio to text for data processing. The text to speech. API converts text into high quality voice audio. And the video intelligence API recognizes motion and action in video. How well a machine learning model is trained depends on how much data is available to train it. As you might expect, Google has lots of images, texts and ML researchers to train its pre trained models. This means less work for you and a faster return on your investment.

2. Let's practice!

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