Alternatives and similar repositories for ds_project_template

Users that are interested in ds_project_template are comparing it to the libraries listed below

• jem1031 / pandas-pipelines-custom-transformers
  Material for Talk at PyData Seattle 2017
  ☆168Updated 7 years ago
• FilippoBovo / production-data-science
  Production Data Science: a workflow for collaborative data science aimed at production
  ☆457Updated 5 years ago
• harnav / pydata-docker-tutorial
  Tutorial given at PyData LA 2018
  ☆96Updated last year
• bgweber / DS_Production
  ☆155Updated 5 years ago
• aayushmnit / cookbook
  A repository of machine learning codes written for re-usability
  ☆141Updated 6 years ago
• tsterbak / pydataberlin-2019
  This Repository contains the material for my tutorial "Managing the end-to-end machine learning lifecycle with MLFlow" at pyData/pyCon Be…
  ☆39Updated 2 years ago
• xLaszlo / datascience-fails
  Collection of articles listing reasons why data science projects fail.
  ☆464Updated 4 years ago
• davified / clean-code-ml
  Clean Code concepts adapted for machine learning and data science. Now a free video series 😎 https://bit.ly/2yGDyqT
  ☆730Updated 4 years ago
• bhargavvader / personal
  Contains Jupyter Notebooks of stuff I am working on.
  ☆197Updated 5 years ago
• ersaurabhverma / autoplotter
  ☆153Updated 5 years ago
• trainindata / testing-and-monitoring-ml-deployments
  Example project for the course "Testing & Monitoring Machine Learning Model Deployments"
  ☆135Updated last year
• Samreay / DSGoPipeline
  A short workshop on datascience pipelines using mlflow and airflow
  ☆53Updated 2 years ago
• alteryx / predict-customer-churn
  A general-purpose framework for solving problems with machine learning applied to predicting customer churn
  ☆423Updated last year
• docker-for-data-science / docker-for-data-science-tutorial
  Materials for "Docker for Data Science" tutorial presented at PyCon 2018 in Cleveland, OH
  ☆160Updated 5 years ago
• MaartenGr / ML-API
  Guide on creating an API for serving your ML model
  ☆65Updated 3 years ago
• klemag / PyconUS_2019-model-interpretability-tutorial
  Content for the Model Interpretability Tutorial at Pycon US 2019
  ☆41Updated last year
• koaning / spacy-youtube-material
  Here are the notebooks used during the spacy youtube series.
  ☆103Updated 4 years ago
• jmugan / modern_practical_nlp
  This course covers how you can use NLP to do stuff.
  ☆267Updated 5 years ago
• mmortazavi / EntityEmbedding-Working_Example
  This repository contains a notebook demonstrating a practical implementation of the so-called Entity Embedding for Encoding Categorical F…
  ☆75Updated 6 years ago
• amueller / dabl
  Data Analysis Baseline Library
  ☆133Updated last year
• yanneta / pytorch-tutorials
  ☆242Updated 2 years ago
• davidsbatista / machine-learning-notebooks
  Assorted exercises and proof-of-concepts to understand and study machine learning and statistical learning theory
  ☆45Updated 7 years ago
• klemag / pydata_nyc2018-intro-to-model-interpretability
  Notebook and slides for my talk at Pydata NYC 2018
  ☆88Updated last year
• chrispaulca / waterfall
  An easy to use waterfall chart function for Python
  ☆164Updated 5 years ago
• cmawer / reproducible-model
  ☆87Updated 6 years ago
• jgoerner / beyond-jupyter
  🐍💻📊 All material from the PyCon.DE 2018 Talk "Beyond Jupyter Notebooks - Building your own data science platform with Python & …
  ☆157Updated 7 years ago
• arimbr / valohai-fasttext-example
  Production Machine Learning Pipeline for Text Classification with fastText
  ☆33Updated 4 years ago
• mattilyra / pydataberlin-2017
  Repo for my talk at the PyData Berlin 2017 conference
  ☆65Updated 8 years ago
• dabl / dabl
  Data Analysis Baseline Library
  ☆727Updated last year
• dipanjanS / deep_transfer_learning_nlp_dhs2019
  Contains the code and deck for the presentation on Applying Deep Transfer Learning for NLP in Analytics Vidhya's DataHack Summit 2019
  ☆83Updated 6 years ago