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| DATE | 2015-09-18 |
| FROM | Ruben Safir
|
| SUBJECT | Subject: [LIU Comp Sci] AI lectures
|
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Date: Fri, 18 Sep 2015 20:53:23 -0400
From: Ruben Safir
To: learn-at-nylxs.com
Subject: [LIU Comp Sci] AI lectures
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Webinar: Forecasting With Predictive Analytics and Data Science
Registration: http://hubs.ly/H019XtK0
*Alternative link: http://info.salford-systems.com/forecasting-webinar
September 22, 10AM - 11AM PDT
* If the time is inconvenient, please register and we will send you a
* recording.
Abstract: Forecasting with predictive analytics offers the opportunity
to leverage the huge amounts of data, now readily available, that
exhibit the following characteristics:
· Data that changes over time, as well as static data
· Perhaps hundreds, thousands of independent variables
· Data reflective of today's ever-changing economic environment
With data mining and machine learning methods, your data can easily and
quickly be converted into knowledge to yield more accurate and more
actionable models. We will demonstrate these techniques on a data set
from a Brazilian grocery store chain. Information including date, store,
promotions, climate, and unit price will be used to predict the total
sales of oranges for the company. The model will help you identify what
affects sales, decide on best prices and promos, and most importantly,
forecast sales in the future.
Additionally, we will go beyond the retail industry and touch on:
Case Studies:
*Forecasting Alaska's Ecosystem in the
22nd Century
*Atmospheric Pollution Forecasting
*Forecasting Recessions with MARS
Although we show 4 examples, the approach is widely applicable and you
will be able to follow the same steps on your own datasets. Examples of
datasets that would benefit include:
· Business: Marketing forecasts, targeted sales forecasts, fraud
detection
· Drug Discovery: forecasting the onset of disease, forecasting
healthcare outcomes
· Insurance: forecasting response to a premium change, forecasting
costs at the onset of a claim
· Environmental: decision making for environmental management,
population dynamics, habitat suitability, forecast weather conditions
throughout
the world
· Epidemiology: risk analysis, population dynamics
This webinar will be a step-by-step presentation that you can repeat on
your own!
Included with Registration:
· Webinar recording
· 30 day software evaluation
· Dataset used in presentation
· Step-by-step instruction for you to try at home
Who should attend:
· Attend if you want to implement data science techniques even
without a data science, statistical or programming background.
· Attend if you want to understand why data science techniques are
so important for forecasting.
Registration: http://hubs.ly/H019XtK0
*Alternative link: http://info.salford-systems.com/forecasting-webinar
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