Python Sagemaker-training Resources

Obs-Causal-Q-Network AAAI 2022 - Training a Resilient Q-Network against Observational Interference Preprint | Slides | Colab Demo | Environment Setup

Intel® Neural Compressor targeting to provide unified APIs for network compression technologies, such as low precision quantization, sparsity, pruning, knowledge distillation, across different deep learning frameworks to pursue optimal inference performance.

Data Science on AWS - O'Reilly Book Get the book on Amazon.com Book Outline Quick Start Workshop (4-hours) In this quick start hands-on workshop, you

This repository is no longer maintained. Please use our new Softlearning package instead. Soft Actor-Critic Soft actor-critic is a deep reinforcement

Introduction This is an implementation of our paper Supervised 3D Pre-training on Large-scale 2D Natural Image Datasets for 3D Medical Image Analysis.

TSLM-DISCOURSE-MARKERS Scope This repository contains: (1) Code to extract discourse markers from wikipedia (TSA). (1) Code to extract significant dis

Deep Learning with TensorFlow and EO Data Complete file set for Jupyter Book Autor: Development Seed Date: 04 October 2021 ISBN: (to come) Notebook tu

Fast Training of Neural Lumigraph Representations using Meta Learning Project Page | Paper | Data Alexander W. Bergman, Petr Kellnhofer, Gordon Wetzst

Distilling-the-knowledge-in-neural-network Teaches a student network from the knowledge obtained via training of a larger teacher network This is an i

offline-training-pipeline This is the offline-training-pipeline for our project. We adopt the offline training and online prediction Machine Learning

March 1, 2021: Service on gitpitch.com has been shutdown permanently. GitPitch 4.0 Docs Twitter About Watch the Introducing GitPitch 4.0 Video Visit t

Π-NAS This repository provides the evaluation code of our submitted paper: Pi-NAS: Improving Neural Architecture Search by Reducing Supernet Training

Learnable Boundary Guided Adversarial Training This repository contains the implementation code for the ICCV2021 paper: Learnable Boundary Guided Adve

Seasonal Contrast: Unsupervised Pre-Training from Uncurated Remote Sensing Data This is the official PyTorch implementation of the SeCo paper: @articl

GPT2-Chinese Description Chinese version of GPT2 training code, using BERT tokenizer or BPE tokenizer. It is based on the extremely awesome repository

AlexNet training on ImageNet LSVRC 2012 This repository contains an implementation of AlexNet convolutional neural network and its training and testin

This repository contains examples and related resources showing you how to preprocess, train, and serve your models using Amazon SageMaker with data fetched from Delta Lake.

Enformer TPU training script (wip) The full training script for Enformer (Tensorflow Sonnet) on TPU clusters, in an effort to migrate the model to pyt

Training DALL-E with volunteers from all over the Internet This repository is a part of the NeurIPS 2021 demonstration "Training Transformers Together

NLU Training Data Crowd-sourced training data for the development and testing of Rasa NLU models. If you're interested in grabbing some data feel free

Image Segmentation with U-Net Algorithm on Carvana Dataset using AWS Sagemaker This is a full project of image segmentation using the model built with

An LSTM Odyssey Code for training variants of "LSTM: A Search Space Odyssey" on Fomoro. Check out the blog post. Training Install TensorFlow. Clone th

Contrastive Unpaired Translation (CUT) video (1m) | video (10m) | website | paper We provide our PyTorch implementation of unpaired image-to-image tra

DeepSIM: Image Shape Manipulation from a Single Augmented Training Sample (ICCV 2021 Oral) Project | Paper Official PyTorch implementation of the pape

Train aug_clip against laion400m-embeddings found here: https://laion.ai/laion-400-open-dataset/ - note that this used the base ViT-B/32 CLIP model. S

TrainingBike Code, models and schematics I've used to interface my stationary training bike with PC. You can find more information about the project i

BasicNeuralNetwork - This project looks over the basic structure of a neural network and how machine learning training algorithms work. For this project, I used the sigmoid function as an activation function along with stochastic gradient descent to adjust the weights and biases.

U2-Net: U Square Net Modified for paired image training of style transfer This is an unofficial repo making use of the code which was made available b

styleGAN2-ADA-training-jupyter Training custom datasets in styleGAN2-ADA on Jupyter Official StyleGAN2-ADA by NIVIDIA Paper Training Generative Advers

CIFAR-10_train-test - training and testing codes for dataset CIFAR-10

opevcvdl-hw3 This project uses pytorch and Qt to achieve the requirements. Version Python 3.6 opencv-contrib-python 3.4.2.17 Matplotlib 3.1.1 pyqt5 5.

Easily train or fine-tune SOTA computer vision models from one training repository. SuperGradients Introduction Welcome to SuperGradients, a free open

EfficientFace Zengqun Zhao, Qingshan Liu, Feng Zhou. "Robust Lightweight Facial Expression Recognition Network with Label Distribution Training". AAAI

Lightning-Hydra-Template A clean and scalable template to kickstart your deep learning project 🚀 ⚡ 🔥 Click on Use this template to initialize new re

Pytorch implementation of paper Semi-supervised Knowledge Transfer for Deep Learning from Private Training Data

PseudoSeg: Designing Pseudo Labels for Semantic Segmentation PseudoSeg is a simple consistency training framework for semi-supervised image semantic s

Semi-Supervised Semantic Segmentation with Cross-Consistency Training (CCT) Paper, Project Page This repo contains the official implementation of CVPR

COResets and Data Subset selection Reduce end to end training time from days to hours (or hours to minutes), and energy requirements/costs by an order

Self-Training for Neural Sequence Generation This repo includes instructions for running noisy self-training algorithms from the following paper: Revi

MarginGAN This repository is the implementation of the paper "MarginGAN: Adversarial Training in Semi-Supervised Learning". 1."preliminary" is the imp

Neural Structured Learning in TensorFlow Neural Structured Learning (NSL) is a new learning paradigm to train neural networks by leveraging structured

Graph Contrastive Learning with Augmentations PyTorch implementation for Graph Contrastive Learning with Augmentations [poster] [appendix] Yuning You*

CCGL: Contrastive Cascade Graph Learning This repo provides a reference implementation of Contrastive Cascade Graph Learning (CCGL) framework as descr

In this project, two programs can help you take full agvantage of time on the model training with a remote server, which can push notification to your phone about the information during model training, like the model indices and unexpected interrupts. Then you can do something in time for your work.

GCC: Graph Contrastive Coding for Graph Neural Network Pre-Training Original implementation for paper GCC: Graph Contrastive Coding for Graph Neural N

Expert-Linking Pytorch implementation of the paper "COAD: Contrastive Pre-training with Adversarial Fine-tuning for Zero-shot Expert Linking." This is

T-Zero This repository serves primarily as codebase and instructions for training, evaluation and inference of T0. T0 is the model developed in Multit

ALPRO Align and Prompt: Video-and-Language Pre-training with Entity Prompts [Paper] Dongxu Li, Junnan Li, Hongdong Li, Juan Carlos Niebles, Steven C.H

Pretrain-Recsys This is our Tensorflow implementation for our WSDM 2021 paper: Bowen Hao, Jing Zhang, Hongzhi Yin, Cuiping Li, Hong Chen. Pre-Training

G-Bert Pre-training of Graph Augmented Transformers for Medication Recommendation Intro G-Bert combined the power of Graph Neural Networks and BERT (B

GPT-GNN: Generative Pre-Training of Graph Neural Networks GPT-GNN is a pre-training framework to initialize GNNs by generative pre-training. It can be

Self-supervised edge features for improved Graph Neural Network training Data availability: Here is a link to the raw data for the organoids dataset.

DrRepair: Learning to Repair Programs from Error Messages This repo provides the source code & data of our paper: Graph-based, Self-Supervised Program

Autoregressive Predictive Coding This repository contains the official implementation (in PyTorch) of Autoregressive Predictive Coding (APC) proposed

Shuffle and Learn (Shuffle Tuple) Created by Ishan Misra Based on the ECCV 2016 Paper - "Shuffle and Learn: Unsupervised Learning using Temporal Order

CoCLR: Self-supervised Co-Training for Video Representation Learning This repository contains the implementation of: InfoNCE (MoCo on videos) UberNCE

There is More than Meets the Eye: Self-Supervised Multi-Object Detection and Tracking with Sound by Distilling Multimodal Knowledge MM-DistillNet is a

AdaFocusV2 This repo contains the official code and pre-trained models for AdaFo

Deep Learning Training Scripts DNN Frameworks Caffe PyTorch Tensorflow CNN Models VGG ResNet DenseNet Inception Language Modeling GatedCNN-LM Attentio

Hub is a dataset format with a simple API for creating, storing, and collaborating on AI datasets of any size. The hub data layout enables rapid transformations and streaming of data while training models at scale. Hub is used by Google, Waymo, Red Cross, Oxford University, and Omdena.

This codebase is being actively maintained, please create and issue if you have issues using it Basics All data files are included under losses and ea

TUPE PyTorch implementation of Rethinking Positional Encoding in Language Pre-training. Quickstart Clone this repository. git clone https://github.com

SLIP: Self-supervision meets Language-Image Pre-training What you can find in this repo: Pre-trained models (with ViT-Small, Base, Large) and code to

Build an Amazon SageMaker Pipeline to Transform Raw Texts to A Knowledge Graph This repository provides a pipeline to create a knowledge graph from ra

Sieve Video Data Collection Example Find samples that are interesting within hours of raw video, for free and completely automatically using Sieve API

DMT: Dynamic Mutual Training for Semi-Supervised Learning This repository contains the code for our paper DMT: Dynamic Mutual Training for Semi-Superv

Introduction This is a Python package available on PyPI for NVIDIA-maintained utilities to streamline mixed precision and distributed training in Pyto

ONNX Runtime is a cross-platform inference and training machine-learning accelerator. ONNX Runtime inference can enable faster customer experiences an

Overview of Kubeflow Fairing Kubeflow Fairing is a Python package that streamlines the process of building, training, and deploying machine learning (

ML Lineage Helper This library is a wrapper around the SageMaker SDK to support ease of lineage tracking across the ML lifecycle. Lineage artifacts in

animeface deep models for anime images. Datasets anime-face-dataset Anime faces collected from Getchu.com. Based on Mckinsey666's dataset. 63.6K image

learned_optimization: Training and evaluating learned optimizers in JAX learned_optimization is a research codebase for training learned optimizers. I

HyperGBM Doc | 中文 We Are Hiring！ Dear folks,we are offering challenging opportunities located in Beijing for both professionals and students who are k

Opacus is a library that enables training PyTorch models with differential privacy. It supports training with minimal code changes required on the cli

Domain-informed Neural Networks Codes for building and training the neural network model described in Domain-informed neural networks for interaction

PTvsBT On the Complementarity between Pre-Training and Back-Translation for Neural Machine Translation (Findings of EMNLP 2021) Citation Please cite a

Vision-aided GAN video (3m) | website | paper Can the collective knowledge from a large bank of pretrained vision models be leveraged to improve GAN t

Fine-grained Post-training for Multi-turn Response Selection Implements the model described in the following paper Fine-grained Post-training for Impr

Neural Volumes This repository contains training and evaluation code for the paper Neural Volumes. The method learns a 3D volumetric representation of

Data-Efficient GANs with DiffAugment project | paper | datasets | video | slides Generated using only 100 images of Obama, grumpy cats, pandas, the Br

SEW (Squeezed and Efficient Wav2vec) The repo contains the code of the paper "Performance-Efficiency Trade-offs in Unsupervised Pre-training for Speec

Sequential Transformer This is a code for training Transformers on sequential tasks such as language modeling. Unlike the original Transformer archite

PEGASUS library Pre-training with Extracted Gap-sentences for Abstractive SUmmarization Sequence-to-sequence models, or PEGASUS, uses self-supervised

Hiring We are hiring at all levels (including FTE researchers and interns)! If you are interested in working with us on NLP and large-scale pre-traine

FlauBERT and FLUE FlauBERT is a French BERT trained on a very large and heterogeneous French corpus. Models of different sizes are trained using the n

ProphetNet-X This repo provides the code for reproducing the experiments in ProphetNet. In the paper, we propose a new pre-trained language model call

ELECTRA Introduction ELECTRA is a method for self-supervised language representation learning. It can be used to pre-train transformer networks using

RangeLoss Pytorch This is a Pytorch reproduction of Range Loss, which is proposed in paper 《Range Loss for Deep Face Recognition with Long-Tailed Trai

Notice: Support for Python 3.6 will be dropped in v.0.2.1, please plan accordingly! Efficient and Scalable Physics-Informed Deep Learning Collocation-

Behavioural-Cloning-in-autonomous-driving Using CNN to mimic the driver based on training data from Torcs. Approach First, the data was collected from

Vit This is a simple program for training and testing vit. Key requirements: torch, torchvision and timm. Dataset I put 5 categories of the cub classi

PantheonRL is a package for training and testing multi-agent reinforcement learning environments. PantheonRL supports cross-play, fine-tuning, ad-hoc coordination, and more.

HETU Documentation | Examples Hetu is a high-performance distributed deep learning system targeting trillions of parameters DL model training, develop

The pokemon showdown Python environment A Python interface to create battling pokemon agents. poke-env offers an easy-to-use interface for creating ru

PyGAD: Genetic Algorithm in Python PyGAD is an open-source easy-to-use Python 3 library for building the genetic algorithm and optimizing machine lear

Training Atari2600 by Reinforcement Learning Train Atari2600 and check how it works! How to Setup You can setup packages on your local env. $ make set

A lightweight library designed to accelerate the process of training PyTorch models by providing a minimal, but extensible training loop which is flexible enough to handle the majority of use cases, and capable of utilizing different hardware options with no code changes required.

Programmatically Build and Manage Training Data Announcement The Snorkel team is now focusing their efforts on Snorkel Flow, an end-to-end AI applicat

Region_Learner The Pytorch implementation for "Video-Text Pre-training with Learned Regions" (arxiv) We are still cleaning up the code further and pre

Maximum Likelihood Training of Score-Based Diffusion Models This repo contains the official implementation for the paper Maximum Likelihood Training o