Python Textual-experiments Resources

pytorch-maml This is a PyTorch implementation of the supervised learning experiments from the paper Model-Agnostic Meta-Learning (MAML): https://arxiv

Flood Detection Challenge This repository contains code for our submission to the ETCI 2021 Competition on Flood Detection (Winning Solution #2). Acco

zalando-pytorch PyTorch experiments with the Zalando fashion-mnist dataset Project Organization ├── LICENSE ├── Makefile - Makefile with co

Alex's PyTorch Personal Trainer (ptpt) (name subject to change) This repository contains my personal lightweight framework for deep learning projects

Textual is a TUI (Text User Interface) framework for Python inspired by modern web development.

🤖 Interactive Machine Learning experiments: 🏋️models training + 🎨models demo

Random Erasing Data Augmentation =============================================================== black white random This code has the source code for

Please use stacknn-core instead! StackNN This project implements differentiable stacks and queues in PyTorch. The data structures are implemented in s

Neural Implicit Reconstruction with Vector Neurons This repository contains code for the neural implicit reconstruction experiments in the paper Vecto

Clockwork VAEs in JAX/Flax Implementation of experiments in the paper Clockwork Variational Autoencoders (project website) using JAX and Flax, ported

Textual is a TUI (Text User Interface) framework for Python using Rich as a renderer. The end goal is to be able to rapidly create rich termin

TSForecasting This repository contains the implementations related to the experiments of a set of publicly available datasets that are used in the tim

Code to run experiments in SLOE: A Faster Method for Statistical Inference in High-Dimensional Logistic Regression. Not an official Google product. Me

Contextualized Perturbation for Textual Adversarial Attack Introduction This is a PyTorch implementation of Contextualized Perturbation for Textual Ad

Deep-Trading Algorithmic trading with deep learning experiments. Now released part one - simple time series forecasting. I plan to implement more soph

Transformer Based Multi-Source Domain Adaptation Dustin Wright and Isabelle Augenstein To appear in EMNLP 2020. Read the preprint: https://arxiv.org/a

VectorAscent: Generate vector graphics from a textual description Example "a painting of an evergreen tree" python text_to_painting.py --prompt "a pai

imgaug This python library helps you with augmenting images for your machine learning projects. It converts a set of input images into a new, much lar

L2X Code for replicating the experiments in the paper Learning to Explain: An Information-Theoretic Perspective on Model Interpretation at ICML 2018,

ReproZip ReproZip is a tool aimed at simplifying the process of creating reproducible experiments from command-line executions, a frequently-used comm

FcaNet-CIFAR An implementation of the paper FcaNet: Frequency Channel Attention Networks on CIFAR10/CIFAR100 dataset. how to run Code: python Cifar.py

gtn_applications An applications library using GTN. Current examples include: Offline handwriting recognition Automatic speech recognition Installing

SciKit-Learn Laboratory This Python package provides command-line utilities to make it easier to run machine learning experiments with scikit-learn. O

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