Cloud-Based Analytics Overview and Tutorial

Cloud-Based Analytics Overview and Tutorial

AIDA presents: Cloud-Based Analytics Overview and Tutorial


When: Tuesday, September 27, 2016, 7:00 – 9:30 PM

Where: Patterson Hall 213

Presenter: Christian Frey, AIDA


Data Analytics and Machine Learning is becoming increasingly accessible via easy to use tools and techniques available on the Web. This means that it is simpler than ever to generate insight and create predictions based on your data without having to purchase and install hardware and software. In this session, you will learn about several data analysis and predictive modeling tools available in your browser. You will learn about some of the benefits and drawbacks of Microsoft Azure Machine Learning Studio, the Google Cloud Predictions API, IBM Analytics, and Amazon Machine Learning. You will participate in a tutorial on BigML, starting with loading in a sample dataset, and then customization of that dataset and model so as to meet your prediction needs. So bring along your Wi-Fi ready laptop and try it for yourself. The use of the BigML cloud-based software is free for datasets up to 16MB, so bring your own data if you wish to try working with it in the second half of the tutorial.

This tutorial is designed for working professionals [AIDA will be offering a student-focused session in the coming weeks]. Participants should be comfortable with basic statistical terms and simple spreadsheets. No prior machine learning experience required, however a review of the following document would provide you with terms that will be used in the session.

Presenter:  Christian Frey, works for AIDA as a Business/Data Analyst. He graduated in May from Acadia University with a Bachelor’s of Business Administration with a major in Computer Science. For AIDA, Christian works with companies to take advantage of their data and use data analytics to improve their business. He also plans events and manages AIDA’s social media presence.

Cost: $10.00+tax to attend. You can register for this event at You should bring a laptop that is Wi-Fi LAN internet ready to participate in the tutorial.  Note: you must register with BigML in advance of the session, so that you are prepared to start in on the exercises with the instructor. You can sign up at Instructions to sign up can be found below.


Instructions for BigML signup:

  1. Navigate to using your favorite modern web browser.
  2. Click on the green “sign up here”, located in the center of your screen.
  3. You have two sign up options:
    1. Use one of the three external login links on the right side, and agree to the permissions request on your chosen website.
    2. Enter your name, e-mail, country, username, and unique password. You can then enter the CAPTCHA, and click “Create an account”. You do not need to enter a promotional code.
  4. You will be automatically logged in, and you are now done. Remember your chosen Username and Password, you will need it during the presentation.



Logistic Regression: A regression where the output is one of two categories, rather than a real number.

Softmax: A generalization of the logisitic regression, where you can have any number of categories.

Decision Tree: A flowchart style tree which can be used to made decisions on data.

Neural Network: A network of nodes and weights which is used to approximate any arbitrary function.

K-means clustering: An algorithm that groups data into K number of categories.


Many thanks to everyone that attended and made the event a success. For those who were unable to attend, you can download the slideshow here.

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