Things on this page are fragmentary and immature notes/thoughts of the author. Please read with your own judgement!
CI/CD for Machine Learning
Things on this page are fragmentary and immature notes/thoughts of the author. Please read with your own judgement!
GitHub Actions
Travis CI
Jenkins
act
Run your GitHub Actions locally.
References
MLOps: Continuous delivery and automation pipelines in machine learning
AI Learning
Things on this page are fragmentary and immature notes/thoughts of the author. Please read with your own judgement!
The picture comes from Machine Learning Algorithms Mindmap.
Feature Engineering
Handling Categorical Variables in Machine Learning
Regularization in Machine Learning Models
Ensemble
Frameworks
Libraries for Gradient Boosting
Big-data (Spark) Friendly Frameworks …
Tips on Feature Engineering for Machine Learning
Things on this page are fragmentary and immature notes/thoughts of the author. Please read with your own judgement!
https://towardsdatascience.com/automatic-feature-engineering-using-deep-learning-and-bayesian-inference-application-to-computer-7b2bb8dc7351
Feature selection Feature extraction Adding features through domain expertise
FeatureTools a Python library for feature engineering Deep neural network can extract features too
whether feature engineering is …
Hyper Parameter Tuning and Automatical Machine Learning
Things on this page are fragmentary and immature notes/thoughts of the author. Please read with your own judgement!
Methodology
hyper-parameter tuning, grid search bayesian optimization evolutionary algorithms genetic programming cross validation k-fold Neural Architecture Search with Reinforcement Learning
Libraries
Optuna
auto-sklearn
Ludwig
Ludwig is a toolbox that allows to …
Tips on Optuna
Things on this page are fragmentary and immature notes/thoughts of the author. Please read with your own judgement!
Optuna is a good framework for hyper parameter tuning in machine learning.