dvgodoy / ML_Fundamentals

Related projects ⓘ

Alternatives and complementary repositories for ML_Fundamentals

• trainindata / testing-and-monitoring-ml-deployments
  Example project for the course "Testing & Monitoring Machine Learning Model Deployments"
  ☆134Updated 8 months ago
• Samreay / DSGoPipeline
  A short workshop on datascience pipelines using mlflow and airflow
  ☆53Updated last year
• eugeneyan / papermill-mlflow
  🧪 Simple data science experimentation & tracking with jupyter, papermill, and mlflow.
  ☆174Updated 4 months ago
• amueller / aml
  Applied Machine Learning with Python
  ☆77Updated 7 months ago
• outerbounds / dsbook
  Code samples for the Effective Data Science Infrastructure book
  ☆110Updated last year
• dmatrix / mlflow-workshop-part-1
  Partly lecture and partly a hands-on tutorial and workshop, this is a three part series on how to get started with MLflow. In this three …
  ☆234Updated 4 years ago
• khuyentran1401 / reproducible-data-science
  Tutorials on creating a reproducible and maintainable data science project
  ☆137Updated 2 years ago
• datarobot-community / examples-for-data-scientists
  ☆60Updated 5 months ago
• khuyentran1401 / customer_segmentation
  An end-to-end project on customer segmentation
  ☆81Updated last year
• eugeneyan / python-collab-template
  🛠 Python project template with unit tests, code coverage, linting, type checking, Makefile wrapper, and GitHub Actions.
  ☆142Updated 6 months ago
• tklouie / PyData_LA_2018
  Added repo for PyData LA 2018 tutorial
  ☆88Updated 5 years ago
• ArjanCodes / 2021-data-science-refactor
  ☆102Updated 2 years ago
• xLaszlo / CQ4DS-notebook-sklearn-refactoring-exercise
  ☆30Updated last year
• jeremyarancio / reservation_cancellation_prediction
  Predict if a reservation will be canceled using robust Machine Learning pipelines with Airflow and Mlflow
  ☆57Updated 9 months ago
• PacktPublishing / Hands-On-Gradient-Boosting-with-XGBoost-and-Scikit-learn
  Hands-On Gradient Boosting with XGBoost and Scikit-learn Published by Packt
  ☆187Updated last year
• KishManani / PyDataLondon2022
  Slides for "Feature engineering for time series forecasting" talk
  ☆57Updated last year
• PacktPublishing / EngineeringMLOps
  Engineering MLOps, published by Packt
  ☆176Updated last year
• amueller / dabl
  Data Analysis Baseline Library
  ☆131Updated 2 weeks ago
• ajhalthor / bayesian-testing
  Notebook to walk through Bayesian testing with Kaggle data
  ☆39Updated 3 years ago
• datarobot-community / tutorials-for-data-scientists
  ☆75Updated last year
• AutoViML / pandas_dq
  Find data quality issues and clean your data in a single line of code with a Scikit-Learn compatible Transformer.
  ☆126Updated 10 months ago
• Bellman281 / Stat4ML
  Statistics and Mathematics for Machine Learning, Deep Learning , Deep NLP
  ☆81Updated 2 years ago
• kaislar / ds_template
  ☆38Updated 2 years ago
• parrt / msds621
  Course notes for MSDS621 at Univ of San Francisco, introduction to machine learning
  ☆348Updated 2 years ago
• bgweber / DS_Production
  ☆155Updated 4 years ago
• eugeneyan / testing-ml
  🔍 Minimal examples of machine learning tests for implementation, behaviour, and performance.
  ☆254Updated 2 years ago
• canyon289 / PyTestforDataScience_PyDataLA
  Pytest for Data Science Beginners
  ☆58Updated 6 years ago
• marvelousmlops / mlops_maturity_assessment
  MLOps maturity assessment
  ☆57Updated last year
• DanilBaibak / ml-in-production
  The practical use-cases of how to make your Machine Learning Pipelines robust and reliable using Apache Airflow.
  ☆53Updated last year
• PacktPublishing / Practical-Deep-Learning-at-Scale-with-MLFlow
  Practical Deep Learning at Scale with MLFlow, published by Packt
  ☆157Updated 11 months ago