Supercharge Your Model Training
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Updated
Aug 11, 2025 - Python
Supercharge Your Model Training
MONeT framework for reducing memory consumption of DNN training
Collection of OSS models that are containerized into a serving container
Integrating Aporia ML model monitoring into a Bodywork serving pipeline.
⌨️ Solutions to Academy Yandex "Тренировки по Machine Learning"
Propensity model training with XGBoost
Self-Hosted MLFlow Docker Image with MySQL and S3 support
MLflow adapter for CrateDB.
Smart Script to Mass Convert PDF .pdf to Markdown .md
learning python day 4
Train a simple text classifier and predict labels - supports ONNX output for performance, language-neutral
Submission of Project
Trainings-pipeline to create a model to digitalising a chess scoresheet
This repository includes jupyter notebooks on CNN for learning or training purposes.
This project Implements the paper “Causal Adversarial Perturbations for Individual Fairness and Robustness in Heterogeneous Data Spaces” using the Python language.
This is a desktop tool to create FSNS datasets. FSNS dataset could be used to train (CNN + seq2seq with visual attention) based OCR.
tracebloc notebook to launch and manage experiments in collaboration
Template designed to kickstart your machine learning projects in Python
Proyecto en el que aplicamos y entrenamos varios modelos de Machine Learning de aprendizaje supervisado de regresión. Y evaluaremos cuál de ellos se adapta mejor a las necesidades de nuestro cliente.
Sample edition of The Stack Enriched: annotated, secure, and optimized code dataset, this is a sample version
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