Introducing


Machine Learning for Developers.

Nexosis makes it easy to start building machine learning applications.

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The Nexosis® Machine Learning Platform

Easy access to a robust suite of time series algorithms

Forecast any data feed
with improved accuracy.

Uncover impact
of internal and external data feeds.

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It's a developers' world.

Nexosis® is all in on the developer experience.
That's why we've tailored our ever expanding documentation to include everything you need to get going.

// Submit dataset
var client = new NexosisClient();
client.DataSets.Create("widget-sales", File.OpenText("C:\\path\\to\\sales-file.csv"));

// Creating a forecast session
var sessionResponse = client.Sessions.CreateForecast(
    "widget-sales",
    "daily_transaction",
    DateTimeOffset.Parse("2017-12-12 10:11:12 -0:00"), 
    DateTimeOffset.Parse("2017-12-22 22:23:24 -0:00"), 
    ResultInterval.Day);

// Retrieve forecast results
using (var output = new StreamWriter(File.OpenWrite("results-file.csv")))
{
    client.Client.Sessions.GetResults(sessionResponse.SavedSessionId, output);
}

// Submit dataset
NexosisClient client = new NexosisClient();
InputStream inputStream = new FileInputStream(new File("./sales-file.csv"));
client.getDataSets().create("widget-sales", inputStream);

// Creating a forecast session
SessionResponse response = nexosisClient.getSessions().createForecast(
    "widget-sales",
    "daily_transaction",
    DateTime.parse("2017-12-12T0:00:00Z"),
    DateTime.parse("2017-12-22T0:00:00Z"),
    ResultInterval.DAY);

// Retrieve forecast results
new File("results-file.csv").createNewFile();
output = new FileOutputStream("results-file.csv");
ReturnsStatus status = nexosisClient.getSessions().getResults(response.getSessionId(), output);

// Submit dataset
const NexosisClient = require('nexosis-api-client').default;
const client = new NexosisClient({key: process.env.NEXOSIS_API_KEY});
client.DataSets.create('widget-sales', readDataFrom(csvFile));

// Create a forecast session
let session = {};
client.Sessions.createForecast(
    'widget-sales', 
    moment().startOf('day'), 
    moment.startOf('day').add(30, 'days'), 
    'sales', 
    'day'
).then(results=>session = results);

// Retrieve forecast results
client.Sessions.results(session.sessionId).then(results=>write(results));

# Submit dataset
client = nexosisapi.Client()
with open('sales-file.csv')) as f:
    result = client.datasets.create_csv('widget-sales', f)

# Create a forecast for the next 30 days on the 'sales' column
session = client.sessions.create_forecast(
    'widget-sales', 
    'daily_transaction', 
    date_parser.parse('2017-12-12 00:00:00 -0:00'), 
    date_parser.parse('2017-12-22 00:00:00 -0:00')
)

# Retrieve forecast results
results = client.sessions.get_results(session.session_id)



// Submit dataset
val client = new NexosisClient()
client.getDataSets.create("widget-sales", new FileInputStream("./sales-file.csv"))

// Creating a forecast session
val session = client.getSessions.createForecast(
  "widget-sales",
  "daily_transaction",
  DateTime.parse("2017-12-12T0:00:00Z"),
  DateTime.parse("2017-12-22T0:00:00Z"),
  ResultInterval.DAY
)

// Retrieve forecast results
val status = client.getSessions.getResults(session.getSessionId, 
    new FileOutputStream("./results-file.csv"))


# Submitting dataset
data = CSV.open('sales-file.csv','rb', headers: true)
NexosisApi.client.create_dataset_csv 'widget-sales', data 

# Creating a forecast session
session  = NexosisApi.client.create_forecast_session(
    'widget-sales',
    '2017-12-12',
    '2017-12-22',
    'daily_transaction'
)

# Retrieve forecast results
results = NexosisApi.client.get_session_results session.sessionId