Slack is a channel-based messaging platform. With Slack, people can work together more effectively, connect all their software tools and services, and find the information they need to do their best work — all within a secure, enterprise-grade environment.
Create a batch prediction given a Supervised Model ID and a Dataset ID. See the docs.
Send a message to a user, group, private channel or public channel. See the documentation
Create a model based on a given source ID, dataset ID, or model ID. See the docs.
Configure custom blocks and send to a channel, group, or user. See the documentation.
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.
The Pipedream Slack app enables you to build event-driven workflows that interact with the Slack API. Once you authorize the Pipedream app's access to your workspace, you can use Pipedream workflows to perform common Slack actions or write your own code against the Slack API.
The Pipedream Slack app is not a typical app. You don't interact with it directly as a bot, and it doesn't add custom functionality to your workspace out of the box. It makes it easier to automate anything you'd typically use the Slack API for, using Pipedream workflows.
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
slack: {
type: "app",
app: "slack",
}
},
async run({steps, $}) {
return await axios($, {
url: `https://slack.com/api/users.profile.get`,
headers: {
Authorization: `Bearer ${this.slack.$auth.oauth_access_token}`,
},
})
},
})
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.
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}`,
},
})
},
})