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Machine Learning and AI Foundations

Classification Modeling

One type of problem absolutely dominates machine learning and artificial intelligence: classification. Binary classification, the predominant method, sorts data into one of two categories: purchase or not, fraud or not, ill or not, etc. Machine learning and AI-based solutions need accurate, well-chosen algorithms in order to perform classification correctly. This course explains why predictive analytics projects are ultimately classification problems, and how data scientists can choose the right strategy (or strategies) for their projects. Instructor Keith McCormick draws on techniques from both traditional statistics and modern machine learning, revealing their strengths and weaknesses. Keith explains how to define your classification strategy, making it clear that the right choice is often a combination of approaches. Then, he demonstrates 11 different algorithms for building out your model, from discriminant analysis to logistic regression to artificial neural networks. Finally, learn how to overcome challenges such as dealing with missing data and performing data reduction.

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    LinkedIn Learning

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    Length 2h
    Starts On Demand (Start anytime)
    Cost $29/month (Access to entire library- free trial available)
    From LinkedIn Learning
    Instructor Keith McCormick
    Download Videos Only via the LinkedIn Learning mobile app
    Language English
    Subjects IT & Networking Data Science
    Tags IT Big Data

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    LinkedIn Learning

    Rating Not enough ratings
    Length 2h
    Starts On Demand (Start anytime)
    Cost $29/month (Access to entire library- free trial available)
    From LinkedIn Learning
    Instructor Keith McCormick
    Download Videos Only via the LinkedIn Learning mobile app
    Language English
    Subjects IT & Networking Data Science
    Tags IT Big Data

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