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{ | |
"metadata": { | |
"name": "" | |
}, | |
"nbformat": 3, | |
"nbformat_minor": 0, | |
"worksheets": [ | |
{ | |
"cells": [ | |
{ |
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import bigml, sys, csv, time | |
from bigml.api import BigML | |
api = BigML(dev_mode=True) | |
source = api.create_source("s3://bigml-public/csv/lc_sample.csv.gz", { "name": "LC Source"} ) | |
api.ok(source) | |
soure = api.get_source(source) | |
lc_dataset = api.create_dataset(source, { "name": "LC Dataset" }) |
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#!/usr/bin/env python | |
import bigml | |
from bigml.api import BigML | |
# You need to define BIGML_USERNAME and BIGML_API_KEY in your environment, or | |
# add them here: | |
#api = BigML(username, api_key, dev_mode=True) | |
api = BigML(dev_mode=True) |
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{ | |
"name": "Moon Phase", | |
"description": "Extends a dataset with a data field to include the moon phase percentage and name.", | |
"inputs": [ | |
{ | |
"name": "dataset-in", | |
"type": "dataset-id", | |
"description": "Dataset for extending with moon phase information." | |
}, | |
{ |
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{ | |
"name": "Lat/Long Distance from a reference point", | |
"description": "Extends a dataset with the distance in meters between lat/long fields and a reference point.", | |
"inputs": [ | |
{ | |
"name": "dataset-in", | |
"type": "dataset-id", | |
"description": "Dataset for extending with distance calculation." | |
}, | |
{ |
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{ | |
"name": "Redfin Deals", | |
"description": "Given a source of sold homes and listed homes, builds a model to predict the price and then shows possible deals.", | |
"inputs": [ | |
{ | |
"name": "redfin-sold-source", | |
"type": "source-id", | |
"description": "Source of sold homes from Redfin." | |
}, | |
{ |
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{ | |
"name": "JSON key/val extraction", | |
"description": "Given a dataset field containing JSON documents and a key, this WhizzML script creates a new feature with the JSON values. This is a hack and *NOT* a valid JSON parser", | |
"inputs": [ | |
{ | |
"name": "dataset-in", | |
"type": "dataset-id", | |
"description": "Dataset to transform by extracting JSON values." | |
}, | |
{ |
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{ | |
"name": "Simple JSON key/val extraction", | |
"description": "Given a dataset field containing JSON documents and a key, this WhizzML script creates a new feature with the JSON values. This is a hack and *NOT* a valid JSON parser", | |
"inputs": [ | |
{ | |
"name": "dataset-in", | |
"type": "dataset-id", | |
"description": "Dataset to transform by extracting JSON values." | |
}, | |
{ |
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{ | |
"name": "Minimum Scale for Cluster Class Purity", | |
"description": "Given a dataset and a categorical field, finds the minimum scale required to create class purity in the cluster with k = number of classes.", | |
"inputs": [ | |
{ | |
"name": "dataset", | |
"type": "dataset-id", | |
"description": "Dataset to analyze." | |
}, | |
{ |
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{ | |
"name": "1-Click Dataset Prefer-it-All", | |
"description": "Given a source, creates a 1-click dataset and then marks all non-preferred field as preferred.", | |
"inputs": [ | |
{ | |
"name": "source", | |
"type": "source-id", | |
"description": "Source to process." | |
} | |
], |
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