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Old 10-11-2017, 04:29 PM
Lisa Solomon Lisa Solomon is offline
Join Date: Nov 2012
College: UCLA, MIT
Posts: 32
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Default Improve your Regression Models with Key Machine Learning Methods

Webinar: Improve your Regression Models with Key Machine Learning Methods (no charge)

  • Methods Discussed: MARS Non-linear Regression, Gradient Boosting, Random Forests
  • LIVE OR ON-DEMAND: Tuesday, October 17th 10AM – 11AM PDT, 1PM EDT
  • ON-DEMAND: If the time is inconvenient, please register and we will send you a recording
  • Duration: 45 minutes followed by Q&A
  • Cost: Complimentary
  • Session 3 of the Webinar Series: Learn How to Make Machine Learning Work. Each session is stand-alone.

Click Here to Register
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Machine learning may sound like an overwhelmingly complicated concept rather than a data-driven method to extract insights that drive future business decisions. To fully utilize machine learning, we first need to understand the benefits to our organization, and the techniques to create models based on questions we need to answer. In this webinar series, we will show you how to easily and automatically apply complex algorithms to data in real world applications.

ALL SESSIONS IN THE WEBINAR SERIES: (Each webinar is stand-alone.)
  • Session 1. ON-DEMAND:
    Data Science: Proven Value in a Variety of Industries
  • Session 2. ON-DEMAND:
    Improve your Classification Models with Key Machine Learning Methods (CART Decision Trees, Gradient Boosting, Random Forests)
  • Session 3. OCTOBER 17:
    Improve your Regression Models with Key Machine Learning Methods (MARS non-linear regression, Gradient Boosting, Random Forests)
  • Session 4. OCTOBER 24:
    Real-world demonstration for the beginner modeler
  • Session 5. OCTOBER 31:
    Real-world demonstration for advanced modelers

Who should attend:
  • Beginners will learn the basics. Data Science techniques that encompass the foundation of data modeling— key methods, building a predictive model, extracting value from complex datasets.
  • Advanced Modelers will continue to evolve their ability to leverage the power of data science. Improve both regression and classification models by utilizing automated features that shorten the time to create an accurate model. We also cover how to better handle missing data, outliers, significant interrelationships among variables that are otherwise hard to capture.

Click Here to Register
Alternate Link:

Can't make it? Sign up and receive the recording!
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data science, machine learning, predictive analytics, regression, statistical modeling

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