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celeb-cnn-project

MLFlow Project used in: https://towardsdatascience.com/create-reusable-ml-modules-with-mlflow-projects-docker-33cd722c93c4

data-science--cheat-sheet

Cheat Sheets

fbtt-embedding

This is a Tensor Train based compression library to compress sparse embedding tables used in large-scale machine learning models such as recommendation and natural language processing. We showed this library can reduce the total model size by up to 100x in Facebook’s open sourced DLRM model while achieving same model quality. Our implementation is faster than the state-of-the-art implementations. Existing the state-of-the-art library also decompresses the whole embedding tables on the fly therefore they do not provide memory reduction during runtime of the training. Our library decompresses only the requested rows therefore can provide 10,000 times memory footprint reduction per embedding table. The library also includes a software cache to store a portion of the entries in the table in decompressed format for faster lookup and process.

horovod

Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet.

lorax

Multi-LoRA inference server that scales to 1000s of fine-tuned LLMs

ludwig

Data-centric declarative deep learning framework

nvtabular

NVTabular is a feature engineering and preprocessing library for tabular data designed to quickly and easily manipulate terabyte scale datasets used to train deep learning based recommender systems.

petastorm

Petastorm library enables single machine or distributed training and evaluation of deep learning models from datasets in Apache Parquet format. It supports ML frameworks such as Tensorflow, Pytorch, and PySpark and can be used from pure Python code.

python_matrix_mul_playground

pytorch-lightning

The lightweight PyTorch wrapper for high-performance AI research. Scale your models, not the boilerplate.

ray

An open source framework that provides a simple, universal API for building distributed applications. Ray is packaged with RLlib, a scalable reinforcement learning library, and Tune, a scalable hyperparameter tuning library.

ray-examples

ray_lightning

Pytorch Lightning Distributed Accelerators using Ray

ray_shuffling_data_loader

A Ray-based data loader with per-epoch shuffling and configurable pipelining, for shuffling and loading training data for distributed training of machine learning models.

test_nvt

Test NVTabular