Python StyleGAN2-ADA-training-jupyter Resources

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

We proposed an unsupervised image-to-image translation method via pre-trained StyleGAN2 network. paper: Unsupervised Image-to-Image Translation via Pr

ipylivebash ipylivebash is a library to run shell script in Jupyter with live ou

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

Nasir Khusraw : Travelling Salesman Problem The TSP solved using genetic algorithm. This project show TSP path overlaid on a map of the Iran provinces

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.

Unofficial Google Colaboratory Notebook and Repository Gallery Please contact me to take over and revamp this repo (it gets around 30k views and 200k

OSMnx Examples OSMnx is a Python package to work with street networks and other spatial data from OpenStreetMap: retrieve, model, analyze, and visuali

earthengine-py-notebooks A collection of 360+ Jupyter Python notebook examples for using Google Earth Engine with interactive mapping Contact: Qiushen

Python for Finance (2nd ed., O'Reilly) This repository provides all Python codes and Jupyter Notebooks of the book Python for Finance -- Mastering Dat

Community repository of bamboolib bamboolib is joining forces with Databricks. For more information, please read our announcement. Please note that th

Fecon235 - Notebooks for financial economics. Keywords: Jupyter notebook pandas Federal Reserve FRED Ferbus GDP CPI PCE inflation unemployment wage income debt Case-Shiller housing asset portfolio equities SPX bonds TIPS rates currency FX euro EUR USD JPY yen XAU gold Brent WTI oil Holt-Winters time-series forecasting statistics econometrics

Recommendation engines are one of the most well known, widely used and highest value use cases for applying machine learning. Despite this, while there are many resources available for the basics of training a recommendation model, there are relatively few that explain how to actually deploy these models to create a large-scale recommender system.

lolviz By Terence Parr. See Explained.ai for more stuff. A very nice looking javascript lolviz port with improvements by Adnan M.Sagar. A simple Pytho

Orbivator_AI Breast Cancer Wisconsin (Diagnostic) GOAL To Determine which features of data (measurements) are most important for diagnosing breast can

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

As much as this series is to educate aspiring computer programmers and data scientists of all ages and all backgrounds, it is also a reminder to mysel

Rendering of live Jupyter notebooks with interactive widgets. Introduction Voilà turns Jupyter notebooks into standalone web applications. Unlike the

Credit-Fraud-Detection - Credit fraud detection in Python using a Jupyter Notebook , using three classification models (Random Forest, Gaussian Naive Bayes, Logistic Regression) from the sklearn library, and judging the performance based on accuracy, precision, recall and f1 score

Curso em Vídeo - Exercícios de Python 3 Sobre o repositório Este repositório contém os notebooks com a listas de exercícios propostos pelo professor G

technical_indicators_cryptos Using technical indicators to find optimal trading strategies to deploy onto trading bot. In the Jup Notebook you wil

Price-Prediction-For-a-Dream-Home ROADMAP TO THIS LINEAR REGRESSION BASED HOUSE PRICE PREDICTION PREDICTION MODEL Import all the dependencies of the p

JupyterNotebook Read, write and execute C, C++, Javascript, Shell scripts, HTML, LaTex in jupyter notebook, And also execute them on remote computer R

This Repo contains a series of Python Jupyter Notebooks and assignments. The assignments are taken from Python Crash Course book by Eric Matthes.

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

Aerial_Distance_Calculator This program can calculate the Aerial Distance between two cities. This repository include both Jupyter notebook and Python

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

Tokern Lineage Engine Tokern Lineage Engine is fast and easy to use application to collect, visualize and analyze column-level data lineage in databas

Poker Game Analysis Analysing poker data from home games with friends. Not a lot of data is collected, so this project is primarily focussed on descri

How to Implement a First-Order Low-Pass Filter in Discrete Time We often teach or learn about filters in continuous time, but then need to implement t

XYZ Spaces for Python Manage your XYZ Hub or HERE Data Hub spaces and Interactive Map Layer from Python. FEATURED IN: Online Python Machine Learning C

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

World Religion Data Visualization Visualization of the World Religion Data dataset by Correlates of War Project. Mostly personal project to famirializ

Analysing aggregated UK polling data The tweet collection & storage pipeline used in email-service is used to also collect tweets from @britainelects.

CADLabs Ethereum Economic Model A modular dynamical-systems model of Ethereum's validator economics, based on the open-source Python library radCAD, a

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

The quick and easy way to add versatile graphical interfaces with networking capabilities to your Python programs. Give instant access to your application to whoever you want on the Internet, without having to deploy it. Works even on your Android smartphone or tablet.

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

Poetry Kernel Use per-directory Poetry environments to run Jupyter kernels. No need to install a Jupyter kernel per Python virtual environment! The id

Jupyter Ascending Sync Jupyter Notebooks from any editor About Jupyter Ascending lets you edit Jupyter notebooks from your favorite editor, then insta

laserbeamsize Simple and fast calculation of beam sizes from a single monochrome image based on the ISO 11146 method of variances. Some effort has bee

discretisedfield Marijan Beg1,2, Martin Lang2, Samuel Holt3, Ryan A. Pepper4, Hans Fangohr2,5,6 1 Department of Earth Science and Engineering, Imperia

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

Population Shift Monitoring popmon is a package that allows one to check the stability of a dataset. popmon works with both pandas and spark datasets.

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 (

databooks is a package for reducing the friction data scientists while using Jupyter notebooks, by reducing the number of git conflicts between different notebooks and assisting in the resolution of the conflicts.

Tensorflow Tutorials using Jupyter Notebook TensorFlow tutorials written in Python (of course) with Jupyter Notebook. Tried to explain as kindly as po

TensorFlow-SIRDS Single Image Random Dot Stereogram for Tensorflow SIRDS is a means to present 3D data in a 2D image. It allows for scientific data di

Python packages Tomas Beuzen & Tiffany Timbers Python packages are a core element of the Python programming language and are how you create organized,

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

Computational Methods for Physics & Astronomy Book version at: https://restrepo.github.io/ComputationalMethods by: Sebastian Bustamante 2014/2015 Dieg

qunomon Description A testbed for testing and managing AI system qualities. Demo Sorry. Not deployment public server at alpha version. Requirement Ins

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

Graph Notebook: easily query and visualize graphs The graph notebook provides an easy way to interact with graph databases using Jupyter notebooks. Us

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