Carles Corbi-Verge ccorbi

## JasonOchoada_Fingerprints.ipynb

      
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                greglandrum
                / JasonOchoada_Fingerprints.ipynb
            
            
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## ds-project-organization.md

      
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                ericmjl
                / ds-project-organization.md
            
            
              Last active
              July 19, 2024 06:49
            
              
                How to organize your Python data science project
              
          
    UPDATE: I have baked the ideas in this file inside a Python CLI tool called pyds-cli. Please find it here: https://github.com/ericmjl/pyds-cli
How to organize your Python data science project

Having done a number of data projects over the years, and having seen a number of them up on GitHub, I've come to see that there's a wide range in terms of how "readable" a project is. I'd like to share some practices that I have come to adopt in my projects, which I hope will bring some organization to your projects.
Disclaimer: I'm hoping nobody takes this to be "the definitive guide" to organizing a data project; rather, I hope you, the reader, find useful tips that you can adapt to your own projects.
Disclaimer 2: What I’m writing below is primarily geared towards Python language users. Some ideas may be transferable to other languages; others may not be so. Please feel free to remix whatever you see here!

  
## residual_network.py
"""
Clean and simple Keras implementation of network architectures described in:
    - (ResNet-50) [Deep Residual Learning for Image Recognition](https://arxiv.org/pdf/1512.03385.pdf).
    - (ResNeXt-50 32x4d) [Aggregated Residual Transformations for Deep Neural Networks](https://arxiv.org/pdf/1611.05431.pdf).

Python 3.
"""

from keras import layers
from keras import models
	"""
	Clean and simple Keras implementation of network architectures described in:
	- (ResNet-50) [Deep Residual Learning for Image Recognition](https://arxiv.org/pdf/1512.03385.pdf).
	- (ResNeXt-50 32x4d) [Aggregated Residual Transformations for Deep Neural Networks](https://arxiv.org/pdf/1611.05431.pdf).

	Python 3.
	"""

	from keras import layers
	from keras import models