with BigML and Pinterest?
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.
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}`,
},
})
},
})
The Pinterest API opens a portal to interact programmatically with Pinterest's rich data, including boards, pins, and user information. By leveraging this API on Pipedream, you can automate actions like posting new pins, extracting pin data for analysis, and synchronizing Pinterest content with other platforms. The potential extends to marketing optimization, content management, and audience engagement, all automated and integrated within the Pipedream ecosystem.
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
pinterest: {
type: "app",
app: "pinterest",
}
},
async run({steps, $}) {
return await axios($, {
url: `https://api.pinterest.com/v5/user_account`,
headers: {
Authorization: `Bearer ${this.pinterest.$auth.oauth_access_token}`,
},
})
},
})