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dmlm-research-and-production's Introduction

Deployment of Machine Learning Models - Code Repository - R&D Section

Python 3.7 License

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This code base corresponds to Sections 2 and 4, where we first develop the machine learning model, and then translate the Jupyter notebooks into production modules.

Table of Contents

  1. Machine Learning Model Development

    1. Data Analysis
    2. Feature Engineering
    3. Feature Selection
    4. Model Building
    5. Recap
  2. Writing Production Code

    1. Procedural Programming
    2. Custom Pipeline
    3. Third Party Pipeline - Open Source Libraries

The rest of the codebase for the course can be found in our other repository

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