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# %% [markdown]
# # Dataiku API Quickstart
#
# ## Load secrets
#
# * Option 1: from environment variables

# %%
DKU_DSS_URL = os.getenv("DKU_DSS_URL")
DKU_API_KEY = os.getenv("DKU_API_KEY")

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begin;

  -- create variables for dataiku role and for database / schema where the tables are (needs to be uppercase for objects)
  set role_name = 'DATAIKU_ROLE';
  set database_name = 'FIVETRAN_DATABASE';
  set schema_name = 'STRIPE';

  use role sysadmin;

  -- grant dataiku access to database

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 begin;

  -- create variables for user / password / role / warehouse / database (needs to be uppercase for objects)
  set role_name = 'DATAIKU_ROLE';
  set user_name = 'DATAIKU_USER';
  set user_password = 'REPLACEME';
  set warehouse_name = 'DATAIKU_WAREHOUSE';
  set database_name = 'DATAIKU_DATABASE';
  set schema_name = 'DATAIKU_SCHEMA';  set stage_name = 'DATAIKU_STAGE';
  

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Machine Learning Kickstart — Training Workshop at PAPIs (Boston — 10/23/17)

Summary

Gain the skills to create ML models and use them in your applications, with open source libraries and cloud platforms. In this workshop, we'll demystify Machine Learning, you'll gain an understanding of its possibilities and limitations, and how to put it to work on real problems. You'll learn to create, evaluate and deploy ML models. We'll adopt a top-down, results-first and experimentation-driven approach.

Registration at papis.io/2017

Learning objectives

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(Note: this is a DRAFT, copied from PAPIs ’16)

Calls and key dates

The call for proposals has officially closed. However, there are slots available for lightning talks (5') on October 11, and we may have gaps in the program open up – feel free to submit your proposal and we'll let you know if an opportunity arises.

1. June 18: Technical and Business Talks
2. July 10: Tutorials and Research Presentations
3. October 11-12: Main conference takes place in Boston

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require 'rubygems'
require 'bundler/setup'
require 'benchmark'

require 'predicsis_ml_sdk'

PredicsisMlSdk.configure do |config|
  config.logger = Logger.new(STDOUT)
  config.logger.level = Logger::WARN
end

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# -*- coding: utf-8 -*-
#
# Copyright (C) 2013 Google Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#      http://www.apache.org/licenses/LICENSE-2.0
#

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Bootstrapping Machine Learning course

Baseline: Learn to use Machine Learning quickly with prediction services and APIs

Duration: 3 days

Who should take this course?

• Companies looking to exploit the value of their data and to use them for decision making
• Developers/hackers who want to acquire new skills and to learn to start building predictive apps

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# -*- mode: ruby -*-
# vi: set ft=ruby :

Vagrant.configure("2") do |config|
  # All Vagrant configuration is done here. The most common configuration
  # options are documented and commented below. For a complete reference,
  # please see the online documentation at vagrantup.com.

  # Every Vagrant virtual environment requires a box to build off of.
  config.vm.box = "lucid32"