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Data Analytics: Regression Models

Data Analytics: Regression Models

Enrolled1.5-3 Hours (Contains Video)
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  • Advanced Level

Data Analytics: Regression Models

This free online takes you through the details the techniques and frameworks used in regression modelling and analysis

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Data Analytics: Regression Models
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Learning Outcomes

Upon successful completion of this course, you will be able to: 

  • Discuss the intuition behind the maximum likelihood estimation theory 
  • Explain the graph of the natural logarithm of the likelihood 
  • Describe the estimation of Poisson and exponential distribution parameter
  • Discuss the python demo for estimation of population parameters for regression equation 
  • Explain the graphical illustration of likelihood contribution 
  • Describe how to build the logistic regression model and equation 
  • Discuss the intuition behind the maximum likelihood estimation theory 
  • Explain the graph of the natural logarithm of the likelihood 
  • Describe the estimation of Poisson and exponential distribution parameter
  • Discuss the python demo for estimation of population parameters for regression equation 
  • Describe the relationship between the odds ratio and the coefficients of independent variables 

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