Python Implicit-q-learning Resources

NeuralForecast is a Python library for time series forecasting with deep learning models. It includes benchmark datasets, data-loading utilities, evaluation functions, statistical tests, univariate model benchmarks and SOTA models implemented in PyTorch and PyTorchLightning.

To create a deep learning model which can explain the content of an image in the form of speech through caption generation with attention mechanism on Flickr8K dataset.

This project proposed the deep learning and image processing method to undertake the diagnosis on 2D CT image and 3D CT volume.

Earthquake detection via fiber optic cables using deep learning Author: Fantine Huot Getting started Update the submodules After cloning the repositor

Classification using Deep Learning Requirements PyTorch version = 1.9.1+cu111 Python version = 3.8.10 PyTorch-Lightning version = 1.4.9 Huggingface

This repository contains the official PyTorch implementation of the "CRF-RNN" semantic image segmentation method, published in the ICCV 2015

Welcome to AirSim AirSim is a simulator for drones, cars and more, built on Unreal Engine (we now also have an experimental Unity release). It is open

IMLE-Net: An Interpretable Multi-level Multi-channel Model for ECG Classification The repostiory consists of the code, results and data set links for

This machine learning model was developed for House Prices - Advanced Regression Techniques competition in Kaggle by using several machine learning models such as Random Forest, XGBoost and LightGBM.

Built various Machine Learning algorithms (Logistic Regression, Random Forest, KNN, Gradient Boosting and XGBoost. etc). Structured a custom ensemble model and a neural network. Found a outperformed model for heart failure prediction accuracy of 88 percent.

Temporal Alignment Prediction for Supervised Representation Learning and Few-Shot Sequence Classification Introduction. This package includes the pyth

This project is a web porting for NVlabs' StyleGAN2, to facilitate exploring all kinds characteristic of StyleGAN networks. Thanks for NVlabs' excelle

AvatarGAN ✨ Generate Cartoon Images using DC-GAN Deep Convolutional GAN is a generative adversarial network architecture. It uses a couple of guidelin

ML Visual Art Colabs A list of cool Colabs on Machine Learning Imagemaking or other artistic purposes 3D Ken Burns Effect Ken Burns Effect by Manuel R

pixel_character_generator Generating retro pixel game characters with Generative Adversarial Networks. Dataset "TinyHero" included. Dataset TinyHero D

Awesome Machine Learning Jupyter Notebooks for Google Colaboratory A curated list of Machine Learning and Deep Learning tutorials in Jupyter Notebook

The unified machine learning framework, enabling framework-agnostic functions, layers and libraries. Contents Overview In a Nutshell Where Next? Overv

pytorch-semseg Semantic Segmentation Algorithms Implemented in PyTorch This repository aims at mirroring popular semantic segmentation architectures i

Semantic Segmentation Suite in TensorFlow. Implement, train, and test new Semantic Segmentation models easily!

Human-Segmentation-PyTorch Human segmentation models, training/inference code, and trained weights, implemented in PyTorch. Supported networks UNet: b

keras-semantic-segmentation-example Example of semantic segmentation in Keras Single class example: Generated data: random ellipse with random color o

YOLTv5 rapidly detects objects in arbitrarily large aerial or satellite images that far exceed the ~600×600 pixel size typically ingested by deep learning object detection frameworks.

ASL-Classifiers American Sign Language (ASL) is a natural language that serves as the predominant sign language of Deaf communities in the United Stat

Distributionally Robust Structure Learning for Discrete Pairwise Markov Networks

VOS This is the source code accompanying the paper VOS: Learning What You Don’t

This project builds a LoRa radio frequency fingerprint identification (RFFI) system based on deep learning techiniques.

Deep learning based model for Cyro ET Sub-tomogram-Detection High degree of stru

Python Assignments for the Deep Learning lectures by Andrew NG on coursera with complete submission for grading capability.

Automating reinforcement learning architecture design for code optimization. Che

ADE20k Semantic segmentation with MAE Getting started Install the mmsegmentation

Training-a-deep-learning-model-on-the-noisy-CIFAR-dataset This repository contai

Brain Weight in Humans Variations of head sizes and brain weights in humans Kaggle dataset obtained from this link by Anubhab Swain. Image obtained fr

CovidcasePrediction A machine learning model for Covid case prediction Problem Statement Using regression algorithms we can able to track the active c

Harmonious Textual Layout Generation over Natural Images via Deep Aesthetics Learning Code for the paper Harmonious Textual Layout Generation over Nat

DirectCLR DirectCLR is a simple contrastive learning model for visual representation learning. It does not require a trainable projector as SimCLR. It

Two-Timescale-DNN Two-Timescale End-to-End Learning for Channel Acquisition and Hybrid Precoding This repository contains the entire code for our work

Soorgeon Join our community | Newsletter | Contact us | Blog | Website | YouTube Convert monolithic Jupyter notebooks into Ploomber pipelines. soorgeo

Tutorial on Amortized Optimization This repository contains the source code for the paper Tutorial on amortized optimization for learning to optimize

Learning Super-Features for Image Retrieval This repository contains the code for running our FIRe model presented in our ICLR'22 paper: @inproceeding

MachineLearning A repository to work on Machine Learning course. Select an algorithm to classify writer's gender, of Hebrew texts. Tested algorithms:

Nash-MTL Official implementation of "Multi-Task Learning as a Bargaining Game". Setup environment conda create -n nashmtl python=3.9.7 conda activate

Used for data processing in machine learning, and help us to construct ML model more easily from scratch. Can be used in linear model, logistic regression model, and decision tree.

Machine Learning from Scratch Author: Shengxuan Wang From: Oregon State University Content: Building Machine Learning model from Scratch, without usin

streamlit-shap This component provides a wrapper to display SHAP plots in Streamlit.

Official codebase for Can Wikipedia Help Offline Reinforcement Learning?

Contrastive Learning for Neural Topic Model This repository contains the impleme

Thumbor-bootcamp - learning and contribution experience with ❤️ and 🤗 from the thumbor team

MoRecon - A tool for reconstructing missing frames in motion capture data.

You Only Cut Once (YOCO) YOCO is a simple method/strategy of performing augmenta

A Microsoft Azure Web App project named Covid 19 Predictor using Machine learning Model (Random Forest Classifier Model ) that helps the user to identify whether someone is showing positive Covid symptoms or not by simply inputting certain values like oxygen level , breath rate , age, Vaccination done or not etc. with the help of kaggle database.

Acceder al código desde Google Colab para poder ver de manera adecuada todas las visualizaciones y poder interactuar con ellas. Links de acceso: Noteb

deSpeckNet-TF-GEE This repository contains the re-implementation of our paper deSpeckNet: Generalizing Deep Learning Based SAR Image Despeckling publi

Wordle Env: A Daily Word Environment for Reinforcement Learning Setup Steps: git pull [email protected]:alex-nooj/wordle_env.git From the wordle_env dire

CNN Detection (CS550 Machine Learning Project) Team Members (Tensor) : Yadava Kishore Chodipilli (11940310) Thashmitha BS (11941250) This is a work do

Our product DrLeaf which not only makes the work easier but also reduces the effort and expenditure of the farmer to identify the disease and its treatment methods. We have to upload the image of an affected plant’s leaf through our website and our plant disease prediction model predicts and returns the disease name. And along with the disease name, we also provide the best suitable methods to cure the disease.

Numerical-Python Numpy NumPy is a library for the Python programming language, adding support for large, multi-dimensional arrays and matrices, along

Mortgage-Application-Analysis Create a machine learning model which will predict if the mortgage will be approved or not based on 5 variables: age, in

TorchGRL TorchGRL is the source code for our paper Graph Convolution-Based Deep Reinforcement Learning for Multi-Agent Decision-Making in Mixed Traffi

To-Be is a machine learning challenge on CodaLab Platform about Mortality Prediction. The challenge aims to adress the problems of medical imbalanced data classification.

NLP - Movie review sentiment analysis The colab notebook contains the code for building a LSTM Recurrent Neural Network that gives 87-88% accuracy on

Tutorial Repository with a minimal example for showing how to deploy training across various compute infrastructure.

spaCy-wrap: For Wrapping fine-tuned transformers in spaCy pipelines spaCy-wrap is minimal library intended for wrapping fine-tuned transformers from t

Continual Learning With Filter Atom Swapping Pytorch Implementation of Continual Learning With Filter Atom Swapping (ICLR'22 Spolight) Paper If find t

GNN_PPI Codes and models for the paper "Learning Unknown from Correlations: Graph Neural Network for Inter-novel-protein Interaction Prediction". Lear

MLOps The MLOps is the process of continuous integration and continuous delivery of Machine Learning artifacts as a software product, keeping it insid

Using DVC with PyCaret & FastAPI (Demo) This repo contains all the resources for my demo explaining how to use DVC along with other interesting tools

Manga OCR Optical character recognition for Japanese text, with the main focus being Japanese manga. It uses a custom end-to-end model built with Tran

DocEnTR Description Pytorch implementation of the paper DocEnTr: An End-to-End Document Image Enhancement Transformer. This model is implemented on to

machine-learning-with-graphs My solutions for Stanford University course CS224W: Machine Learning with Graphs Fall 2021 colabs Course materials can be

CorrelAid Machine Learning Winter School Welcome to the CorrelAid ML Winter School! Task The problem we want to solve is to classify trees in Roosevel

Computer-Vision-Paper-Reviews Computer Vision Paper Reviews with Key Summary along Papers & Codes. Jonathan Choi 2021 The repository provides 100+ Pap

Ray Vector Environment Wrapper You would like to use Ray to vectorize your environment but you don't want to use RLLib ? You came to the right place !

SNCSE SNCSE: Contrastive Learning for Unsupervised Sentence Embedding with Soft Negative Samples This is the repository for SNCSE. SNCSE aims to allev

🤖 AI Awesome Project Template 👋 Template author You may want to adjust badge links in a README.md file. 💎 Installation with pip Installation is as

Evolution Gym A large-scale benchmark for co-optimizing the design and control of soft robots. As seen in Evolution Gym: A Large-Scale Benchmark for E

dino-vit-features [paper] [project page] Official implementation of the paper "Deep ViT Features as Dense Visual Descriptors". We demonstrate the effe

Resnet as representation for Reinforcement Learning (RRL) is a simple yet effective approach for training behaviors directly from visual inputs. We demonstrate that features learned by standard image classification models are general towards different task, robust to visual distractors, and when used in conjunction with standard Imitation Learning or Reinforcement Learning pipelines can efficiently acquire behaviors directly from proprioceptive inputs.

DART Implementation for ICLR2022 paper Differentiable Prompt Makes Pre-trained Language Models Better Few-shot Learners. Environment [email protected] Use pi

TIANCHI Purchase Redemption Forecast Challenge

Fundamentals-of-Machine-Learning This repository introduces the basics of machine learning algorithms for preprocessing, regression and classification

This program takes and input of an ECG in European Data Format (EDF) and outputs the classification for heartbeats into normal vs different types of arrhythmia . It uses a deep learning model for classification purposes.

NLP-Natural-Language-Processing NLP applications using deep learning like text generation etc. 1- Poetry Generation: Using a collection of Irish Poem

Multi-label classification of retinal disorders This is a deep learning course project. The goal is to develop a solution, using computer vision techn

FedML: A Research Library and Benchmark for Federated Machine Learning 📄 https://arxiv.org/abs/2007.13518 News 2021-02-01 (Award): #NeurIPS 2020# Fed

Machine Learning e Data Science com Python Arquivos do curso de Data Science e Machine Learning com Python na Udemy, cliqe aqui para acessá-lo. O prin

PlainML Painless Machine Learning Library for python based on scikit-learn. Install pip install plainml Example from plainml import KnnModel, load_ir

Self-supervised learning Self-supervised learning algorithms provide a way to train Deep Neural Networks in an unsupervised way using contrastive loss

Implicit Regularization in Hierarchical Tensor Factorization and Deep Convolutional Neural Networks. Code, based on the PyTorch framework, for reprodu

DecisionTransformer_StepbyStep Intro Decision Transformer: A brand new Offline RL Pattern. 这是关于NeurIPS 2021 热门论文Decision Transformer的复现。 👍 原文地址: Deci

Bayesian Modeling and Uncertainty Quantification for Learning to Optimize: What, Why, and How TensorFlow implementation for Bayesian Modeling and Unce

Using Self-Supervised Pretext Tasks for Active Learning - Official Pytorch Implementation Experiment Setting: CIFAR10 (downloaded and saved in ./DATA

NaturalCC NaturalCC is a sequence modeling toolkit that allows researchers and developers to train custom models for many software engineering tasks,

Near-Optimal Sparse Allreduce for Distributed Deep Learning (published in PPoPP'22) Ok-Topk is a scheme for distributed training with sparse gradients

CoINN: Correlated-informed neural networks: a new machine learning framework to predict pressure drop in micro-channels Accurate pressure drop estimat

Reinforcement Learning Theory Book (rus)

Readme File for "Using Machine Learning to Test Causal Hypotheses in Conjoint Analysis" by Ham, Imai, and Janson. (2022) All scripts were written and

HealthGen: Conditional EHR Time Series Generation This repository contains the implementation of the HealthGen model, a generative model to synthesize

MetaTTE: a Meta-Learning Based Travel Time Estimation Model for Multi-city Scenarios This is the official TensorFlow implementation of MetaTTE in the

CNN-Filter-DB An Empirical Investigation of Model-to-Model Distribution Shifts in Trained Convolutional Filters Paul Gavrikov, Janis Keuper Paper: htt

DROPO: Sim-to-Real Transfer with Offline Domain Randomization Gabriele Tiboni, Karol Arndt, Ville Kyrki. This repository contains the code for the pap