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Practical Data Science

Application Development

Python Application Setup
- Application Setup using setup.py
Docker

Python Best Practices

How to Write Docstrings
- Creating Rich Documentation With Sphinx

Data and Representation

Data and Representation
Introduction

Practical ML

Practical Machine Learning
- This article was written on Jupyter Notebook
- Imbalanced Classification

Notebooks

Introduction to Notebooks
Google Colab

CI/CD/CT

Continuous Integration, Delivery and Training
GitHub Actions
- GPU Integration Tests Using Kaggle

Version Control

Version Control
Checkout to specific tag

Repository
Open issue

.md

Practical Machine Learning

Practical Machine Learning#

This section of the book details practical considerations when using Machine Learning models. Knowledge of the models discussed will be assumed.

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This article was written on Jupyter Notebook

By Yousef Nami

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