What do you want to automate
with BigML and Zip Archive API?
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Popular BigML and Zip Archive API Actions#
Create a batch prediction given a Supervised Model ID and a Dataset ID. See the docs.
Compress files provided through URLs into a zip folder. See the documentation
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.
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}`,
},
})
},
})
Overview of Zip Archive API#
The Zip Archive API allows you to manage zip archives programmatically. You can create, extract, and modify zip files, making it ideal for automating routine file management tasks. Integrating this API with Pipedream enables you to automate workflows that involve file compression or decompression, combine it with triggers from other apps, and process large batches of files efficiently, saving time and reducing manual effort.
Connect Zip Archive API#
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
zip_archive_api: {
type: "app",
app: "zip_archive_api",
}
},
async run({steps, $}) {
const data = {
"file": `https://www.learningcontainer.com/wp-content/uploads/2020/05/sample-zip-file.zip`,
}
return await axios($, {
method: "post",
url: `https://api.archiveapi.com/extract`,
headers: {
"Accept": `text/plain`,
},
params: {
secret: `${this.zip_archive_api.$auth.secret}`,
},
data,
})
},
})
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