Python StyleGAN2-ADA-training-jupyter Resources

WPPNets: Unsupervised CNN Training with Wasserstein Patch Priors for Image Superresolution This code belongs to the paper [1] available at https://arx

LongScientificFormer For encoding a text longer than 512 tokens, for example 800. Set max_pos to 800 during both preprocessing and training. Some code

Interpretable Control Exploration and Counterfactual Explanation (ICE) on StyleGAN Which Style Makes Me Attractive? Interpretable Control Discovery an

Using Attention in HRL Framework for training options with different attention mechanism and using them to solve downstream tasks. Requirements GPU re

Identifying a Training-Set Attack’s Target Using Renormalized Influence Estimation By: Zayd Hammoudeh and Daniel Lowd Paper: Arxiv Preprint Coming soo

Post-training Quantization for Neural Networks with Provable Guarantees Authors: Jinjie Zhang ([email protected]), Yixuan Zhou ([email protected]) and Ray

This Repository is an up-to-date version of Harvard nlp's Legacy code and a Refactoring of the jupyter notebook version as a shell script version.

SAS: Self-Augmentation Strategy for Language Model Pre-training This repository

SWAG: Supervised Weakly from hashtAGs This repository contains SWAG models from the paper Revisiting Weakly Supervised Pre-Training of Visual Percepti

CST Code release for "Cycle Self-Training for Domain Adaptation" (NeurIPS 2021) Prerequisites torch=1.7.0 torchvision qpsolvers numpy prettytable tqd

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

cell_counting_v2 The repository includes the code for training cell counting applications. (Keras + Tensorflow) Dataset can be downloaded here : http:

Segmentation Training Pipeline This package is a part of Musket ML framework. Reasons to use Segmentation Pipeline Segmentation Pipeline was developed

A Memory Tracer For PyTorch OOM is a nightmare for PyTorch users. However, most

ARM This jupyter notebook project was completed by me and my friend using the dataset from Kaggle. The world Happiness 2017, which ranks 155 countries

First steps with Python in Life Sciences This course material is part of the "First Steps with Python in Life Science" three-day course of SIB-trainin

Machine-Learning with python (jupyter) 머신러닝 야학 작심 10일과 쥬피터 노트북 기반 데이터 사이언스 시작 들어가기전 https://nbviewer.org/ 페이지를 통해서 쥬피터 노트북 내용을 볼 수 있다. 위 페이지에서 현재 레포 기

Collapse by Conditioning: Training Class-conditional GANs with Limited Data Moha

ESGD-M - A stochastic non-convex second order optimizer, suitable for training deep learning models, for PyTorch

Create charts with Python in a very similar way to creating charts using Chart.js. The charts created are fully configurable, interactive and modular and are displayed directly in the output of the the cells of your jupyter notebook environment.

neon_course This repository contains several jupyter notebooks to help users learn to use neon, our deep learning framework. For more information, see

Dive into Machine Learning Hi there! You might find this guide helpful if: You know Python or you're learning it 🐍 You're new to Machine Learning You

This repository contains Jupyter notebooks implementing the algorithms found in the book and summary of the textbook.

Flower-timeout Repo for investigation of timeouts that happens with prolonged training on clients. This repository is meant purely for demonstration o

GitHub-Actions-Docker-training Training exercise repository for GitHub Actions using a docker base. This repository should be cloned and used for trai

Building Shazam from scratch In this repository we tried to implement a simplified copy of the Shazam application able to tell you the name of a song

Circuit Training: An open-source framework for generating chip floor plans with distributed deep reinforcement learning. Circuit Training is an open-s

X-VLM: learning multi-grained vision language alignments Multi-Grained Vision Language Pre-Training: Aligning Texts with Visual Concepts. Yan Zeng, Xi

ColossalAI-Examples This repository contains examples of training models with Co

SQL-query Use SQL query in a jupyter notebook! The table I used can be found on UN Data. Or you can just click the link and download the file undata_s

A novel Engagement Detection with Multi-Task Training (ED-MTT) system which minimizes MSE and triplet loss together to determine the engagement level of students in an e-learning environment.

TiP-Adapter: Training-free CLIP-Adapter for Better Vision-Language Modeling This is the official code release for the paper 'TiP-Adapter: Training-fre

VIOLET: End-to-End Video-Language Transformers with Masked Visual-token Modeling A PyTorch implementation of VIOLET Overview VIOLET is an implementati

py Repository to store sample Python programs. This repository is meant for beginners to assist them in their learning of Python. The repository cover

Gender-classification This is a ML model to classify Male and Females using some physical characterstics Data. Python Libraries like Pandas,Numpy and

ffcv ImageNet Training A minimal, single-file PyTorch ImageNet training script designed for hackability. Run train_imagenet.py to get... ...high accur

Welcome to Carbon Insight Carbon Insight is a platform aiming to display the carbon neutralization roadmap for researchers, decision-makers, and other

Find Line Detection (Image Processing) Identifying lanes of the road is very common task that human driver performs. It's important to keep the vehicl

GraphMLTutorialNLDL22 Tutorial NLDL22: Introduction to Graph Machine Learning, with Jupyter notebooks This tutorial takes place during the conference

This project is for finding a solution to use Security Onion Elastic data with Jupyter Notebooks. The goal is to successfully use this notebook project below with Security Onion for beacon detection capabilities.

Moshpit SGD: Communication-Efficient Decentralized Training on Heterogeneous Unreliable Devices This repository contains the official PyTorch implemen

Scraping-test-matches-data This is a Web scraping project using BeautifulSoup and Python to scrape basic information of all the Test matches played ti

This is the implementation of "Training deep neural networks via direct loss minimization" published at ICML 2016 in PyTorch. The implementation targe

Pianote Pianote is an application that helps musicians practice piano ear traini

Monitor deep learning model training and hardware usage from mobile. 🔥 Features Monitor running experiments from mobile phone (or laptop) Monitor har

Mercury Share your Python notebooks with others Easily convert your Python notebooks into interactive web apps by adding parameters in YAML. Simply ad

BRATS 2021 Solution For Segmentation Task This repo contains the supported pytorch code and configuration files to reproduce 3D medical image segmenta

Morpheus-Deblend This repo generates the training data and the model for Morpheus-Deblend. This is the active development repo for the project and as

Real Time Object Recognition From your Screen Desktop . In this post, I will explain how to build a simply program to detect objects from you desktop

Semi-Supervised Learning with Multi-Head Co-Training (PyTorch) Abstract Co-training, extended from self-training, is one of the frameworks for semi-su

Pyasmtools - looking at the python bytecode for fun and profit. The pyasmtools library is made up of two parts A python bytecode disassembler . See Py

Reinforcement Learning Project This project was created to make it easier to get started with Reinforcement Learning. It now contains: An implementati

ff-neural-network A Python module for the generation and training of an entry-level feedforward neural network. This repository serves as a repurposin

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.

FACE-DETECTION-ATTENDENCE-SYSTEM Made in Jupyter(Anaconda) notebook. Language Used: Python Steps to perform before running the program : Install Anaco

Designed a greedy algorithm based on Markov sequential decision-making process in MATLAB/Python to optimize using Gurobi solver, the wheel size, gear shifting sequence by modeling drivetrain constraints to achieve maximum laps in a race with a 2-hour time window.

Python Machine Learning Jupyter Notebooks (ML website) Dr. Tirthajyoti Sarkar, Fremont, California (Please feel free to connect on LinkedIn here) Also

CFD Python Please cite as: Barba, Lorena A., and Forsyth, Gilbert F. (2018). CFD Python: the 12 steps to Navier-Stokes equations. Journal of Open Sour

deep-learning-with-keras-notebooks 這個github的repository主要是個人在學習Keras的一些記錄及練習。希望在學習過程中發現到一些好的資訊與範例也可以對想要學習使用 Keras來解決問題的同好，或是對深度學習有興趣的在學學生可以有一些方便理解與上手範例

Text2Code for Jupyter notebook A proof-of-concept jupyter extension which converts english queries into relevant python code. Blog post with more deta

Master the essential skills needed to recognize and solve complex real-world problems with Machine Learning and Deep Learning by leveraging the highly popular Python Machine Learning Eco-system.

2019-indian-election-eda Exploratory Data Analysis of the 2019 Indian General Elections using a dataset from Kaggle. This project is a part of the Cou

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

Python pandas Q&A video series Read about the series, and view all of the videos on one page: Easier data analysis in Python with pandas. Jupyter Note

HOUSING PRICE PREDICTION USING MACHINE LEARNING DESCRIPTION Housing Price Prediction Using Machine Learning is to predict the data of housings. Here I

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

Based on 2021 stack overflow data, this machine learning web application helps one predict the salary based on years of experience, level of education and the country they work in.

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

DAT8 Course Repository Course materials for General Assembly's Data Science course in Washington, DC (8/18/15 - 10/29/15). Instructor: Kevin Markham (

Creative Applications of Deep Learning w/ Tensorflow This repository contains lecture transcripts and homework assignments as Jupyter Notebooks for th

GAT - Graph Attention Network (PyTorch) 💻 + graphs + 📣 = ❤️ This repo contains a PyTorch implementation of the original GAT paper ( 🔗 Veličković et

https://covid19dashboards.com This project was built with fastpages Background This project showcases how you can use fastpages to create a static das

Spark Python Notebooks This is a collection of IPython notebook/Jupyter notebooks intended to train the reader on different Apache Spark concepts, fro

Hands-on-Machine-Learning 目的 这份笔记旨在帮助中文学习者以一种较快较系统的方式入门机器学习， 是在学习Hands-on Machine Learning with Scikit-Learn and TensorFlow这本书的 时候做的个人笔记: 此项目的可取之处 原书的

Python for Finance (O'Reilly) This repository provides all Python codes and Jupyter Notebooks of the book Python for Finance -- Analyze Big Financial

Jupyter Notebook tutorials on solving real-world problems with Machine Learning & Deep Learning using PyTorch. Topics: Face detection with Detectron 2, Time Series anomaly detection with LSTM Autoencoders, Object Detection with YOLO v5, Build your first Neural Network, Time Series forecasting for Coronavirus daily cases, Sentiment Analysis with BERT.

Deepo is a series of Docker images that allows you to quickly set up your deep learning research environment supports almost all commonly used deep le

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

Customer Service Requests Analysis Project 1 DESCRIPTION Background of Problem Statement : NYC 311's mission is to provide the public with quick and e

PyExplainer PyExplainer is a local rule-based model-agnostic technique for generating explanations (i.e., why a commit is predicted as defective) of J

Machine Learning Study 혼자 해보기 기여자 (Contributors) ✨ Teddy Lee 🏠 HongJaeKwon 🏠 Seungwoo Han 🏠 Tae Heon Kim 🏠 Steve Kwon 🏠 SW Song 🏠 K1A2 🏠 Wooil

Think Bayes 2 by Allen B. Downey The HTML version of this book is here. Think Bayes is an introduction to Bayesian statistics using computational meth

Machine Learning in Asset Management If you like this type of content then visit ML Quant site below: https://www.ml-quant.com/ Part One Follow this l

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

ContainDS Dashboards for JupyterHub A Dashboard publishing solution for Data Science teams to share results with decision makers. Run a private on-pre

Automatic summarization is the process of shortening a text document with software, in order to create a summary with the major points of the original document. Technologies that can make a coherent summary take into account variables such as length, writing style and syntax.

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