with BigML and Google Vertex AI?
Create a batch prediction given a Supervised Model ID and a Dataset ID. See the docs.
Examines an image or video following given instructions. Results will contain the analysis findings. See the documentation
Create a model based on a given source ID, dataset ID, or model ID. See the docs.
Analyzes a specified text for its underlying sentiment. See the documentation
Create a source with a provided remote URL that points to the data file that you want BigML to download for you. See the docs.
The BigML API offers a suite of machine learning tools that enable the creation and management of datasets, models, predictions, and more. It's a powerful resource for developers looking to incorporate machine learning into their applications. Within Pipedream, you can leverage the BigML API to automate workflows, process data, and apply predictive analytics. By connecting BigML to other apps in Pipedream, you can orchestrate sophisticated data pipelines that react to events, perform analyses, and take action based on machine learning insights.
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
bigml: {
type: "app",
app: "bigml",
}
},
async run({steps, $}) {
return await axios($, {
url: `https://bigml.io/andromeda/source`,
params: {
username: `${this.bigml.$auth.username}`,
api_key: `${this.bigml.$auth.api_key}`,
},
})
},
})
With the Google Vertex AI API, you can tap into a robust suite of AI tools offered by Google Cloud to build, deploy, and scale machine learning models. Whether you're processing data, training custom models, or using pre-trained ones, Vertex AI provides a unified platform for AI development. In Pipedream, you can create serverless workflows that interact with Vertex AI, allowing you to automate tasks like model training, prediction, and resource management without provisioning your own infrastructure.
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
google_vertex_ai: {
type: "app",
app: "google_vertex_ai",
}
},
async run({steps, $}) {
return await axios($, {
url: `https://www.googleapis.com/oauth2/v1/userinfo`,
headers: {
Authorization: `Bearer ${this.google_vertex_ai.$auth.oauth_access_token}`,
},
})
},
})