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with actiTIME and BigML?
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Popular Ways to Connect actiTIME with BigML#
Popular actiTIME and BigML Triggers#
Emit new event when a new customer is created. See the documentation
Emit new event when a new task is created. See the documentation
Emit new event when the user's working time is updated. See the documentation
Popular actiTIME and BigML Actions#
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.
Changes the existing leave time record with a given value in actiTIME. See the documentation
Connect actiTIME#
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
actitime: {
type: "app",
app: "actitime",
}
},
async run({steps, $}) {
return await axios($, {
url: `${this.actitime.$auth.url}/api/v1/users`,
auth: {
username: `${this.actitime.$auth.email}`,
password: `${this.actitime.$auth.password}`,
},
})
},
})
Overview of BigML#
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.
Connect BigML#
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}`,
},
})
},
})
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