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README.md

DS-SF-30 | Unit Project 3: Machine Learning Modeling

Submission:

  • Please push your assignment to your fork (your GitHub repository of the course) and submit a link to it via the form shared in Slack.

PROMPT

In this project, you will perform a logistic regression on the admissions data we've been working with in projects 1 and 2.

Objective: Completed Jupyter notebook that includes basic modeling using logistic regression.

DELIVERABLES

Completed Jupyter Notebook

  • Requirements:
    • Create one-hot encoding using binary variables.
    • Calculate odds ratios by hand.
    • Complete a logistic regression using statsmodels and interpret your findings.
    • Calculate predicted probabilities.
    • Do a similar analysis using sklearn.

RESOURCES

Dataset

The dataset is available here.

Starter code

Review the questions in the starter code notebook provided.

Suggestions for Getting Started

  • Review logistic regression, odds ratios and probabilities from prior lessons.
  • Read the documenation for statsmodels and sklearn. Most of the time, there is a tutorial that you can follow; learning to read documentation is crucial to your success as a data scientist.

Additional Links

EVALUATION

The rubric is available here.