Building A Predictive Model

  • April 1, 2010 · 7:00 PM
  • Bluefly

We will discuss in technical detail how to build a predictive model for product recommendations to increase revenue and improve customer experience. If you are interested in building your own predictive model, this meetup is for you. Light refreshments will be served. NOTE: This presentation will expand on the topics discussed in our first meetup, and go into greater detail.

Presented by Alex Lin, Sr. Architect of Intelligent Mining
Networking: 6:30 pm - 7:00 pm
Presentation: 7:00 pm - 7:45 pm

Topics we will cover:
1. Predictive modeling methodology
2. k-Nearest Neighbor (kNN) machine learning algorithm
3. Singular value decomposition (SVD) method for dimensionality reduction
4. Using a synthetic data set to improve your model

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  • A former member
    A former member

    Great attendance, presentation, and discussion, but I might be considered biased :) Thanks again to everyone who came out to make it happen!

    April 2, 2010

  • Yin A.

    Great presentation. I thought presenting the topics as experiments was a great way to go. I would suggest being careful about using acronyms when describing various machine learning techniques. I couldn't remember the exact references in the last slide, but I would plug the IEEE Internet Computing paper from January/ February 2003 titled " recommendations: Item to Item Collaborative Filtering" as a great high level overview paper.

    April 2, 2010

  • Alex L.

    Nice. It is available in the lastest version 0.3 (March 16)

    April 2, 2010

  • Otis G.

    I double-checked Mahout. SVD is in there:
    * Parallel Lanczos SVD(Singular Value Decomposition) solver.

    See also:­

    April 2, 2010

  • Otis G.

    Good and entertaining presentation.

    April 1, 2010

  • alex p.

    Alex did a good job in walking through basics of building a predictive model. It was very informative and the conversation generated was great.

    April 1, 2010

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