BigML

Machine Learning made beautifully simple. A company-wide platform that runs in any cloud or on-premises to operationalize Machine Learning in your organization.

Integrate the BigML API with the HTTP / Webhook API

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

Create Batch Prediction with BigML API on New Requests from HTTP / Webhook API
HTTP / Webhook + BigML
 
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Create Model with BigML API on New Requests from HTTP / Webhook API
HTTP / Webhook + BigML
 
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Create Source (Remote URL) with BigML API on New Requests from HTTP / Webhook API
HTTP / Webhook + BigML
 
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Create Batch Prediction with BigML API on New Requests (Payload Only) from HTTP / Webhook API
HTTP / Webhook + BigML
 
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Create Model with BigML API on New Requests (Payload Only) from HTTP / Webhook API
HTTP / Webhook + BigML
 
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New Requests from the HTTP / Webhook API

Get a URL and emit the full HTTP event on every request (including headers and query parameters). You can also configure the HTTP response code, body, and more.

 
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New Requests (Payload Only) from the HTTP / Webhook API

Get a URL and emit the HTTP body as an event on every request

 
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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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New event when the content of the URL changes. from the HTTP / Webhook API

Emit new event when the content of the URL changes.

 
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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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Send any HTTP Request with the HTTP / Webhook API

Send an HTTP request using any method and URL. Optionally configure query string parameters, headers, and basic auth.

 
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Send GET Request with the HTTP / Webhook API

Send an HTTP GET request to any URL. Optionally configure query string parameters, headers and basic auth.

 
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Connect BigML

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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}`,
      },
    })
  },
})

Connect HTTP / Webhook

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// To use any npm package on Pipedream, just import it
import axios from "axios"

export default defineComponent({
  async run({ steps, $ }) {
    const { data } = await axios({
      method: "GET",
      url: "https://pokeapi.co/api/v2/pokemon/charizard",
    })
    return data.species
  },
})

Community Posts

A Look at Pipedream
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Building a Traffic-Based Workflow in Pipedream
Building a Traffic-Based Workflow in Pipedream
Normally I don't like to blog about stuff that isn't generally available to all, but as it will be available sometime soon, I decided to go ahead anyway. And I built something really cool I want to share so that's another reason to talk about this now!