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Buffalo, NY /

Content based and Collaborative Filtering Recommendation Systems

Delaware North HQ 250 Delaware Ave , Buffalo, NY (map)

More details will be posted shortly.

This is a rough outline of what I plan to cover.

• What is a recommender system (RS)?

-- a.k.a RecSys, Recommendation Engine, (RE)

-- Where we find RS

• Motivating factors behind RS development

• The most commonly found RS

- Content Based (CB) Recommenders

-- Philosophy & Design Approach

-- Building a CB RS (code & math)

-- Example

- Collaborative Filtering (CF) Recommenders

-- Philosophy & Design Approach

--- Implicit vs Explicit Rating

-- Building a CF RS (code & math)

-- Methods of CF: Memory Based, Model Based

-- Example

- When is a RS considered successful?

-- Accuracy isn't everything

-- Target reveals pregnancy

- CB RS and CF RS: side by side comparisson

- Hybrid RS

• What to bring

Nothing planned at this time.

• Important to know

I plan to make this presentation accessible to as wide of an audience as possible. Those with little to no background in mathematics or machine learning should be able to follow along quite easily.

Submitted by

Eightbit-59902de7-98ba-42d1-a922-49a369f68e3b Brett Langdon

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