MLLite's repositories
sklearn2sql-demo
Demo of an In-database processing tool for scikit-learn
sklearn_explain
Model explanation provides the ability to interpret the effect of the predictors on the composition of an individual score.
pytorch2sql
Deep Learning (PyTorch) Models Deployment using SQL databases
sklearn2sql_heroku
Heroku web service client for sklearn2sql
presentations_slides
Presentations , Slides
reproducible_random
A python random number generator that can be reproduced across hardware and software platforms. Based on the C++ standard random number generator (std::mt19937) . Source only.
scikit-learn_reproducible_randoms
Scikit-Learn Special Fork for MLLite Prototyping (2023-09)
TinyML_On_MicroControllers_Demo
Demo of a prototype using MLLite for training and deployment of Machine Learning Models on various devices and microcontrollers.
xgboost_reproducible_randoms
XGBoost Special Fork for MLLite Prototyping (2023-11)
mllite_validation_logs
Data/Output/Logs of the MLLite Validation Process : JSON output, SQL generation, Perf comparison with Legacy Models, ...
sklearn2json
A tool to jsonify some sklearn and xgboost models. A high level serialization that works across programming languages. Used for mllite tests.