Key Steps in Starting Your First Predictive Analytics Project - Webinar By EITAGlobal
Date: | 14-Jan-14 to 14-Jan-14 |
Location: | Online Event / Fremont / California / United States |
Category: | Technology Conferences & Trade Fairs |
Overview: Predictive Analytics (PA) is an approach to analysis that has moved from being a niche approach to a mainstream approach and is often included in lists of growing technology industries. Many analysts are familiar with building basic analyses and reports in Excel, KPIs with a Business Intelligence (BI) tool, or statistical tests. PA, however, is not an approach than can be summarized by a series of rules or recipes: there is certainly science behind PA approaches, but there is also considerable "art" as well.
The "art" of PA is driven by principles derived from the science, but still allows for multiple approaches to achieve the same end. This webinar summarizes the best practices for building predictive models including both the art and the science of PA during each stage of the process, including Data Understanding, Data Preparation, Predictive Modeling and Deployment.
Why should you attend: Effective predictive modeling does not require a PhD in mathematics, statistics, or hard science fields to do well. Many effective and even famous data miners and predictive modelers have BS or BA degrees in non-technical fields. However, it does require a qualitative understanding of what algorithms do, what their limitations are, how to change their behavior, and what kind of data is necessary for building predictive models.
Areas Covered in the Session:
Data Needed for Predictive Modeling
Data Preparation
Top Modeling Algorithms: Decision Tree, Neural Networks, Regression, Clustereing
How to Assess Models
Model Deployment
The "art" of PA is driven by principles derived from the science, but still allows for multiple approaches to achieve the same end. This webinar summarizes the best practices for building predictive models including both the art and the science of PA during each stage of the process, including Data Understanding, Data Preparation, Predictive Modeling and Deployment.
Why should you attend: Effective predictive modeling does not require a PhD in mathematics, statistics, or hard science fields to do well. Many effective and even famous data miners and predictive modelers have BS or BA degrees in non-technical fields. However, it does require a qualitative understanding of what algorithms do, what their limitations are, how to change their behavior, and what kind of data is necessary for building predictive models.
Areas Covered in the Session:
Data Needed for Predictive Modeling
Data Preparation
Top Modeling Algorithms: Decision Tree, Neural Networks, Regression, Clustereing
How to Assess Models
Model Deployment
Visitors
Who Will Benefit:
Business Analyst
Marketing Analyst
Business Analyst
Marketing Analyst
Exhibitors
We are EITAGlobal, a continuing professional education provider with a difference. We believe that coming from a responsible and professional continuing professional education provider in the IT industry space; our trainings have to carry a premier value.
We have devised a strategy of making trainings extremely effective and relevant by bringing Experts and participants across the table. In line with this philosophy, we ensure that a high proportion of our trainings are in the form of live, in-person seminars and Consulting.
We have devised a strategy of making trainings extremely effective and relevant by bringing Experts and participants across the table. In line with this philosophy, we ensure that a high proportion of our trainings are in the form of live, in-person seminars and Consulting.
EIN News
provides powerful, real-time media monitoring, news aggregation & syndication services. Read the latest news about this topic. See:
- 3D Printing News Today
- Apple Samsung Patent War News
- Biotechnology News Today
- CeBIT News Today
- Conferences & Trade Shows Today
- Consumer Electronics Show News Today
- EMS News Today
- Game Developers Conference News Today
- Nanotechnology News Today
- Satellites News Today
- Semiconductor Industry Today
- Smartwatch News Today
- Technology Today
- Web 2.0 News Today