MLSpace: Hassle-free machine learning & deep learning development

Related tags

Deep Learningdockermachine-learningdeep-learningjupytercudacudnncode-server
Overview

MLSpace

Hassle-Free Machine Learning & Deep Learning Development

  • No need to worry about CUDA
  • No need to worry about cuDNN
  • No need to worry about TensorFlow version
  • No need to worry about PyTorch version
  • No need to install any libraries

coming soon

NOTE: PRs are currently not accepted. All PRs will be closed. Please use issues instead.

Owner
abhishek thakur
Kaggle: www.kaggle.com/abhishek
abhishek thakur
GitHub Repository https://mlspace.readthedocs.io/en/latest/
Fast and Easy Infinite Neural Networks in Python

Neural Tangents ICLR 2020 Video | Paper | Quickstart | Install guide | Reference docs | Release notes Overview Neural Tangents is a high-level neural

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Simple-System-Convert--C--F - Simple System Convert With Python

Simple-System-Convert--C--F REQUIREMENTS Python version : 3 HOW TO USE Run the c

Jonathan Santos 2 Feb 16, 2022
Official PyTorch implementation of the paper "Likelihood Training of Schrödinger Bridge using Forward-Backward SDEs Theory (SB-FBSDE)"

Official PyTorch implementation of the paper "Likelihood Training of Schrödinger Bridge using Forward-Backward SDEs Theory (SB-FBSDE)" which introduces a new class of deep generative models that gene

Guan-Horng Liu 43 Jan 03, 2023
A selection of State Of The Art research papers (and code) on human locomotion (pose + trajectory) prediction (forecasting)

A selection of State Of The Art research papers (and code) on human trajectory prediction (forecasting). Papers marked with [W] are workshop papers.

Karttikeya Manglam 40 Nov 18, 2022
Code of paper "CDFI: Compression-Driven Network Design for Frame Interpolation", CVPR 2021

CDFI (Compression-Driven-Frame-Interpolation) [Paper] (Coming soon...) | [arXiv] Tianyu Ding*, Luming Liang*, Zhihui Zhu, Ilya Zharkov IEEE Conference

Tianyu Ding 95 Dec 04, 2022
Code, Data and Demo for Paper: Controllable Generation from Pre-trained Language Models via Inverse Prompting

InversePrompting Paper: Controllable Generation from Pre-trained Language Models via Inverse Prompting Code: The code is provided in the "chinese_ip"

THUDM 101 Dec 16, 2022
[CVPR2021 Oral] FFB6D: A Full Flow Bidirectional Fusion Network for 6D Pose Estimation.

FFB6D This is the official source code for the CVPR2021 Oral work, FFB6D: A Full Flow Biderectional Fusion Network for 6D Pose Estimation. (Arxiv) Tab

Yisheng (Ethan) He 201 Dec 28, 2022
Evolution Strategies in PyTorch

Evolution Strategies This is a PyTorch implementation of Evolution Strategies. Requirements Python 3.5, PyTorch = 0.2.0, numpy, gym, universe, cv2 Wh

Andrew Gambardella 333 Nov 14, 2022
Pretrained SOTA Deep Learning models, callbacks and more for research and production with PyTorch Lightning and PyTorch

Pretrained SOTA Deep Learning models, callbacks and more for research and production with PyTorch Lightning and PyTorch

Pytorch Lightning 1.4k Jan 01, 2023
Scribble-Supervised LiDAR Semantic Segmentation, CVPR 2022 (ORAL)

Scribble-Supervised LiDAR Semantic Segmentation Dataset and code release for the paper Scribble-Supervised LiDAR Semantic Segmentation, CVPR 2022 (ORA

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Contrastive Language-Image Pretraining

CLIP [Blog] [Paper] [Model Card] [Colab] CLIP (Contrastive Language-Image Pre-Training) is a neural network trained on a variety of (image, text) pair

OpenAI 11.5k Jan 08, 2023
Implements an infinite sum of poisson-weighted convolutions

An infinite sum of Poisson-weighted convolutions Kyle Cranmer, Aug 2018 If viewing on GitHub, this looks better with nbviewer: click here Consider a v

Kyle Cranmer 26 Dec 07, 2022
A library to inspect itermediate layers of PyTorch models.

A library to inspect itermediate layers of PyTorch models. Why? It's often the case that we want to inspect intermediate layers of a model without mod

archinet.ai 380 Dec 28, 2022
Deploy optimized transformer based models on Nvidia Triton server

🤗 Hugging Face Transformer submillisecond inference 🤯 and deployment on Nvidia Triton server Yes, you can perfom inference with transformer based mo

Lefebvre Sarrut Services 1.2k Jan 05, 2023
LoveDA: A Remote Sensing Land-Cover Dataset for Domain Adaptive Semantic Segmentation (NeurIPS2021 Benchmark and Dataset Track)

LoveDA: A Remote Sensing Land-Cover Dataset for Domain Adaptive Semantic Segmentation by Junjue Wang, Zhuo Zheng, Ailong Ma, Xiaoyan Lu, and Yanfei Zh

Kingdrone 174 Dec 22, 2022
Annotate datasets with a semi-trained or fully trained YOLOv5 model

YOLOv5 Auto Annotator Annotate datasets with a semi-trained or fully trained YOLOv5 model Prerequisites Ubuntu =20.04 Python =3.7 System dependencie

Akash James 3 May 14, 2022
a delightful machine learning tool that allows you to train, test and use models without writing code

igel A delightful machine learning tool that allows you to train/fit, test and use models without writing code Note I'm also working on a GUI desktop

Nidhal Baccouri 3k Jan 05, 2023
No Code AI/ML platform

NoCodeAIML No Code AI/ML platform - Community Edition Video credits: Uday Kiran Typical No Code AI/ML Platform will have features like drag and drop,

Bhagvan Kommadi 5 Jan 28, 2022
Companion code for the paper "An Infinite-Feature Extension for Bayesian ReLU Nets That Fixes Their Asymptotic Overconfidence" (NeurIPS 2021)

ReLU-GP Residual (RGPR) This repository contains code for reproducing the following NeurIPS 2021 paper: @inproceedings{kristiadi2021infinite, title=

Agustinus Kristiadi 4 Dec 26, 2021
(3DV 2021 Oral) Filtering by Cluster Consistency for Large-Scale Multi-Image Matching

Scalable Cluster-Consistency Statistics for Robust Multi-Object Matching (3DV 2021 Oral Presentation) Filtering by Cluster Consistency (FCC) is a very

Yunpeng Shi 11 Sep 28, 2022