Integrate the Pipedream API with the BigML API

Setup the Pipedream API trigger to run a workflow which integrates with the BigML API. Pipedream's integration platform allows you to integrate Pipedream and BigML remarkably fast. Free for developers.

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Popular Ways to Connect Pipedream with BigML#

Create Batch Prediction with BigML API on New Scheduled Tasks from Pipedream API

Pipedream + BigML

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Create Model with BigML API on New Scheduled Tasks from Pipedream API

Pipedream + BigML

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Create Source (Remote URL) with BigML API on New Scheduled Tasks from Pipedream API

Pipedream + BigML

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Create a Subscription with Pipedream API on New Model Created from BigML API

BigML + Pipedream

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Create a Subscription with Pipedream API on New Prediction Made from BigML API

BigML + Pipedream

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Popular Pipedream and BigML Triggers#

New Scheduled Tasks from the Pipedream API

Exposes an HTTP API for scheduling messages to be emitted at a future time

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New Upcoming Event Alert from the Pipedream API

Emit new event based on a time interval before an upcoming event in the calendar. This source uses Pipedream's Task Scheduler. See the documentation for more information and instructions for connecting your Pipedream account.

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Card Due Date Reminder from the Pipedream API

Emit new event at a specified time before a card is due.

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New Model Created from the BigML API

Emit new event for every created model. See docs here.

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New Prediction Made from the BigML API

Emit new event for every made prediction. See docs here.

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Popular Pipedream and BigML Actions#

Create Batch Prediction with the BigML API

Create a batch prediction given a Supervised Model ID and a Dataset ID. See the docs.

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Create Model with the BigML API

Create a model based on a given source ID, dataset ID, or model ID. See the docs.

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Create Source (Remote URL) with the BigML API

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.

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Create a Subscription with the Pipedream API

Create a Subscription. See Doc

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Delete a Subscription with the Pipedream API

Delete a Subscription. See Doc

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Overview of Pipedream#

Pipedream is an API that allows you to build applications that can connect to
various data sources and processes them in real-time. You can use Pipedream to
create applications that can perform ETL (Extract, Transform, and Load) tasks,
as well as to create data-driven workflows.

Some examples of applications you can build using the Pipedream API include:

An application that can extract data from a database, transform it, and then
load it into another database.
An application that can monitor a data source for changes, and then trigger a
workflow in response to those changes.
An application that can poll an API for new data, and then process that data
in real-time.

Connect Pipedream#

import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    pipedream: {
      type: "app",
      app: "pipedream",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `https://api.pipedream.com/v1/users/me`,
      headers: {
        Authorization: `Bearer ${this.pipedream.$auth.api_key}`,
      },
    })
  },
})

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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