Alternatives and similar repositories for Machine-Learning-for-High-Risk-Applications-Book

Users that are interested in Machine-Learning-for-High-Risk-Applications-Book are comparing it to the libraries listed below

• PacktPublishing / Practical-Deep-Learning-at-Scale-with-MLFlow
  Practical Deep Learning at Scale with MLFlow, published by Packt
  ☆162Updated last year
• GokuMohandas / monitoring-ml
  Learn how to monitor ML systems to identify and mitigate sources of drift before model performance decay.
  ☆89Updated 2 years ago
• KishManani / PyDataLondon2022
  Slides for "Feature engineering for time series forecasting" talk
  ☆61Updated 2 years ago
• PacktPublishing / Machine-Learning-for-Streaming-Data-with-Python
  Machine Learning for Streaming Data with Python, published by Packt
  ☆71Updated last year
• khuyentran1401 / cicd-mlops-demo
  Demo for CI/CD in a machine learning project
  ☆110Updated 2 years ago
• GokuMohandas / testing-ml
  Learn how to create reliable ML systems by testing code, data and models.
  ☆88Updated 2 years ago
• PacktPublishing / Applied-Machine-Learning-Explainability-Techniques
  Applied Machine Learning Explainability Techniques, published by Packt
  ☆244Updated last year
• PacktPublishing / Machine-Learning-Model-Serving-Patterns-and-Best-Practices
  Machine Learning Model Serving Patterns and Best Practices
  ☆35Updated last year
• KishManani / m5-forecasting-tutorial
  An end-to-end tutorial to forecast the M5 dataset using feature engineering pipelines and gradient boosting.
  ☆19Updated 2 years ago
• PacktPublishing / Machine-Learning-Engineering-with-Python
  Machine Learning Engineering with Python
  ☆185Updated 2 years ago
• khuyentran1401 / customer_segmentation
  An end-to-end project on customer segmentation
  ☆83Updated 2 years ago
• data-max-hq / ab-testing-in-ml
  Deploy A/B testing infrastructure in a containerized microservice architecture for Machine Learning applications.
  ☆40Updated 7 months ago
• VincentGranville / Main
  Main folder. Material related to my books on synthetic data and generative AI. Also contains documents blending components from several f…
  ☆96Updated 11 months ago
• BexTuychiev / tricking-data-science
  A book of subtle code tricks and gem resources for all things data, machine learning and deep learning.
  ☆168Updated 11 months ago
• gkunapuli / ensemble-methods-notebooks
  A collection of companion Jupyter notebooks for Ensemble Methods for Machine Learning (Manning, 2023)
  ☆88Updated 2 years ago
• mattharrison / effective_xgboost_book
  ☆286Updated 2 years ago
• vinyluis / Articles
  References to the Medium articles
  ☆87Updated 2 years ago
• PacktPublishing / Comet-for-Data-Science
  Comet for Data Science, published by Packt
  ☆42Updated last year
• GokuMohandas / feature-store
  Using a feature store to connect the DataOps and MLOps workflows to enable collaborative teams to develop efficiently.
  ☆57Updated 2 years ago
• Paulescu / build-and-deploy-real-time-feature-pipeline
  Develop and deploy a real-time feature pipeline in Python, using Bytewax 🐝 and Hopsworks Feature Store.
  ☆134Updated 2 years ago
• derevirn / pycaret-book
  Repository for the book Simplifying Machine Learning with PyCaret.
  ☆66Updated 2 years ago
• shanakaChathu / churn_model
  ☆22Updated 2 years ago
• AutoViML / pandas_dq
  Find data quality issues and clean your data in a single line of code with a Scikit-Learn compatible Transformer.
  ☆131Updated last year
• PacktPublishing / Production-Ready-Applied-Deep-Learning
  Production-Ready Applied Deep Learning
  ☆90Updated last year
• BenWilson2 / ML-Engineering
  Reference code base for ML Engineering, Manning Publications
  ☆133Updated 4 years ago
• ThinamXx / MLOps
  The repository contains a list of projects which I will work on while learning and implementing MLOps.
  ☆79Updated 2 years ago
• PacktPublishing / Machine-Learning-Engineering-with-MLflow
  Machine Learning Engineering with MLflow, published by Packt
  ☆117Updated last year
• visenger / Awesome-ML-Model-Governance
  This repository provides a curated list of references about Machine Learning Model Governance, Ethics, and Responsible AI.
  ☆116Updated last year
• GokuMohandas / data-engineering
  Construct a modern data stack and orchestration the workflows to create high quality data for analytics and ML applications.
  ☆223Updated 2 years ago
• khuyentran1401 / reproducible-data-science
  Tutorials on creating a reproducible and maintainable data science project
  ☆146Updated 3 years ago