What do you want to automate
with BigML and Data Stores?
Prompt, edit and deploy AI agents that connect to BigML, Data Stores and 2,500+ other apps in seconds.
Trusted by 1,000,000+ developers from startups to Fortune 500 companies
Popular Ways to Connect BigML with Data Stores#
Popular BigML and Data Stores Actions#
Create a batch prediction given a Supervised Model ID and a Dataset ID. See the docs.
Add or update a single record in your Pipedream Data Store
Create a model based on a given source ID, dataset ID, or model ID. See the docs.
Add or update multiple records to your Pipedream Data Store
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 Data Stores#
Data Stores are a key-value store that allow you to persist state and share data across workflows. You can perform CRUD operations, enabling dynamic data management within your serverless architecture. Use it to save results from API calls, user inputs, or interim data; then read, update, or enrich this data in subsequent steps or workflows. Data Stores simplify stateful logic and cross-workflow communication, making them ideal for tracking process statuses, aggregating metrics, or serving as a simple configuration store.
Connect Data Stores#
export default defineComponent({
props: {
myDataStore: {
type: "data_store",
},
},
async run({ steps, $ }) {
await this.myDataStore.set("key_here","Any serializable JSON as the value")
return await this.myDataStore.get("key_here")
},
})Trusted by 1,000,000+ developers from startups to Fortune 500 companies