with BigML and Fauna?
Create a batch prediction given a Supervised Model ID and a Dataset ID. See the docs.
Create a model based on a given source ID, dataset ID, or model ID. See the docs.
Performs an arbitrary authorized GraphQL query. See docs here
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}`,
},
})
},
})
Fauna API offers a powerful serverless database solution for modern applications. Its unique capabilities allow for highly scalable, secure, and flexible data management. With Pipedream, you can harness the power of Fauna to create intricate serverless workflows that react to various triggers, manage data efficiently, and connect seamlessly with other services and APIs to automate complex tasks.
module.exports = defineComponent({
props: {
faunadb: {
type: "app",
app: "faunadb",
}
},
async run({steps, $}) {
const faunadb = require('faunadb')
const q = faunadb.query
const client = new faunadb.Client({ secret: this.faunadb.$auth.secret })
// Lists collections in the database tied to your secret key
const collectionsPaginator = await client.paginate(q.Collections())
this.collections = []
await collectionsPaginator.each(page => {
for (const collection of page) {
this.collections.push(collection.id)
}
})
},
})