Python Model-visualization Resources

FAST is an open-source cross-platform framework with the main goal of making it easier to do high-performance processing and visualization of medical images on heterogeneous systems utilizing both multi-core CPUs and GPUs. To achieve this, FAST use modern C++, OpenCL and OpenGL.

Customizing Visual Styles in Plotly Code for a workshop originally developed for an Unconference session during the Outlier Conference hosted by Data

PyTorch NeRF and pixelNeRF NeRF: Tiny NeRF: pixelNeRF: This repository contains minimal PyTorch implementations of the NeRF model described in "NeRF:

Price Prediction model is used to develop an LSTM model to predict the future market price of Bitcoin and Ethereum.

It is mainly for data visualization projects of Atmospheric Science, Marine Science, Environmental Science or other majors.

PyTorch Implementation of the SuRP algorithm by the authors of the AISTATS 2022 paper "An Information-Theoretic Justification for Model Pruning".

Cement-Strength-Prediction Problem Statement To build a regression model to predict the concrete compressive strength based on the different features

Energy_Output_Predictor Artificial Neural network regression model to predict the energy output in a combined cycle power plant. Abstract Energy outpu

RE results graph visualization and company clustering Installation pip install -r requirements.txt python -m nltk.downloader stopwords python3.7 main.

py-self-organizing-maps Simple implementation of self-organizing maps (SOMs) A SOM is an unsupervised method for learning a mapping from a discrete ne

Project: Netflix Data Analysis and Visualization with Python Table of Contents General Info Installation Demo Usage and Main Functionalities Contribut

This repository provides a custom DeepStack model that has been trained detecting ONLY the USPS logo. This was created after I discovered that the Deepstack OpenLogo custom model I was using did not contain USPS.

Rank-One Model Editing (ROME) This repository provides an implementation of Rank-One Model Editing (ROME) on auto-regressive transformers (GPU-only).

ExORL: Exploratory Data for Offline Reinforcement Learning This is an original PyTorch implementation of the ExORL framework from Don't Change the Alg

CBO’s CapTax Model CBO uses its Capital Tax model (CBO-CapTax) to estimate the effects of federal taxes on capital income from new investment. Specifi

SuperGen The source code for Generating Training Data with Language Models: Towards Zero-Shot Language Understanding. Requirements Before running, you

Data Analysis: Data Visualization of Airlines Anderson Cruz | London-UK | Linkedin | Nowa Capital Project: Traffic Airlines Airline Reporting Carrier

⏱ pytorch-benchmark Easily benchmark model inference FLOPs, latency, throughput, max allocated memory and energy consumption Install pip install pytor

LabelImg LabelImg is a graphical image annotation tool. It is written in Python and uses Qt for its graphical interface. Annotations are saved as XML

Doubly Robust Off-Policy Evaluation for Ranking Policies under the Cascade Behavior Model About This repository contains the code to replicate the syn

Pruner for nested cross-validation - Sphinx-Doc Nested cross-validation is necessary to avoid biased model performance in embedded feature selection i

HCSC: Hierarchical Contrastive Selective Coding This repository provides a PyTorch implementation and model weights for HCSC (Hierarchical Contrastive

SentiMent Analysis In this project I built a model to classify movie reviews fromn the IMDB dataset of 50K reviews. WordtoVec : Neural networks only w

Convert Pytorch model to onnx or tflite, and the converted model can be visualized by Netron

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 script is responsible for the operation of the program, it is responsible for both creating the GUI and the process of processing images from dicom files. The program is based on the use of the PyQt5 library, on the basis of which the entire interface containing the appropriate buttons and functions was created.

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

Python inverse kinematics for your robot model based on Pinocchio.

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.

🔥 Olympics Data Analysis 🔥 In Data Science field, there is a big topic before creating a model for future prediction is Data Analysis. We can find o

Data-Visualization-Projects Collection of data visualizing projects through Tableau, Data Wrapper, and Power BI Indigenous-Brands-Social-Movements Pyt

R-YOLOv4 This is a PyTorch-based R-YOLOv4 implementation which combines YOLOv4 model and loss function from R3Det for arbitrary oriented object detect

ONNX-GLPDepth - Python scripts for performing monocular depth estimation using the GLPDepth model in ONNX

Example script to visualize topographic data, earthquake data, and tomographic data on a map

Anomaly-detection-Feature-Selection Evaluate on three different ML model for feature selection using Breast cancer data. ML models: SVM, KNN and MLP.

Breast cancer is been classified into benign tumour and malignant tumour. Logistic regression is applied in this model.

Breast Cancer Classification Model is applied on a different dataset

VOODOO Revealing supercooled liquid beyond lidar attenuation Explore the docs » Report Bug · Request Feature Table of Contents About The Project Built

News-Recommendation-system-using-Bert4Rec-model Bert4rec for news Recommendation

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

This is a model made out of Neural Network specifically a Convolutional Neural Network model. This was done with a pre-built dataset from the tensorflow and keras packages. There are other alternative libraries that can be used for this purpose, one of which is the PyTorch library.

SUMO - Slim U-Net trained on MODA Implementation of the SUMO (Slim U-Net trained on MODA) model as described in: TODO: add reference to paper once ava

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

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

GraphNLI: A Graph-based Natural Language Inference Model for Polarity Prediction in Online Debates Vibhor Agarwal, Sagar Joglekar, Anthony P. Young an

bct_file_generator_for_EasyGSH The aim is to extract timeseries water level 2D information for any designed boundaries within the EasyGSH model domain

chem: collection of mostly python code for molecular visualization, QM/MM, FEP,

This repository contains the raw dataset used in NHNet [1] for the task of News Story Headline Generation. The code of data processing and training is available under Tensorflow Models - NHNet.

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.

Contrastive Learning for Neural Topic Model This repository contains the impleme

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. Link de acceso: https:

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

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

Low-resource-Machine-Translation This repository contains the code for the project relative to the course Deep Natural Language Processing. The goal o

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

Jarvis_voiceAssistance This is a working model for which I have used python. This model can: 1)Play a video or song on youtube. 2)Tell us time. 3)Tell

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

Driver Analysis with Factors and Forests: An Automated Data Science Tool using Python 📊

Transformers are all you need In this workshop we will be exploring NLP state of the art transformers, with SOTA models like T5 and BERT, then build a

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

Mito Monorepo Mito is a spreadsheet that lives inside your JupyterLab notebooks. It allows you to edit Pandas dataframes like an Excel file, and gener

ruCLIP-SB RuCLIP-SB (Russian Contrastive Language–Image Pretraining SWIN-BERT) is a multimodal model for obtaining images and text similarities and re

Data-Analysis-Web-App Data Analysis Web App can analysis data in multiple formates(csv, txt, xls, xlsx, ods, odt) and gives shows you the analysis in

FlatTN This repository contains code accompanying the paper "An End-to-End Chinese Text Normalization Model based on Rule-Guided Flat-Lattice Transfor

SPLADE 🍴 + 🥄 = 🔎 This repository contains the weights for four models as well as the code for running inference for our two papers: [v1]: SPLADE: S

Gesture_recognition The training data consists of a few hundred videos categorised into one of the five classes. Each video (typically 2-3 seconds lon

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.

RVM_onnx_compose RobustVideoMatting and background composing in one model by using onnxruntime. Usage pip install -r requirements.txt python infer_cam

Fake_news_classification A model to classify a piece of news as REAL or FAKE. This python project of detecting fake news deals with fake and real news

MusicYOLO MusicYOLO framework uses the object detection model, YOLOX, to locate notes in the spectrogram. Its performance on the ISMIR2014 dataset, MI

ae_attendances_modelling This repository contains the raw data and a python notebook to ingest historical A&E attendance data and then use a simple Pr

GPT-2 Catalan playground and scripts to train a GPT-2 model either from scrath or from another pretrained model.

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

High-fidelity 3D Model Compression based on Key Spheres This repository contains the implementation of the paper: Yuanzhan Li, Yuqi Liu, Yujie Lu, Siy

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

Open-Source Toolbox for Infrastructures Probabilistic Deterioration Modelling OpenIPDM is a MATLAB open-source platform that stands for infrastructure

UPMT Generate fine-tuning samples & Fine-tuning the model & Generate samples by transferring Note On See main.py as an example: from model import PopM

CvT2DistilGPT2 Improving Chest X-Ray Report Generation by Leveraging Warm-Starting This repository houses the implementation of CvT2DistilGPT2 from [1

Combinatorial model of ligand-receptor binding The binding of ligands to receptors is the starting point for many import signal pathways within a cell

coldcuts coldcuts is an R package that allows you to draw and plot automatically segmentations from 3D voxel arrays. The name is inspired by one of It

Official code of Team Yao at Multi-Modal-Fact-Verification-2022 A Multi-Modal Fact Verification dataset released as part of the De-Factify workshop in

Variational Model Inversion Attacks Kuan-Chieh Wang, Yan Fu, Ke Li, Ashish Khisti, Richard Zemel, Alireza Makhzani Most commands are in run_scripts. W

MIL Model Agnostic Interpretability This repo contains the code for "Model Agnostic Interpretability for Multiple Instance Learning". Overview Executa

asciiMOL A basic molecule viewer written in Python, using curses; Thus, meant for linux terminals. This is an alpha version, featuring: Opening defaul

shap-hypetune A python package for simultaneous Hyperparameters Tuning and Features Selection for Gradient Boosting Models. Overview Hyperparameters t

The purpose of this project is create a classification model capable of accurately predicting the price of secondhand cars. The data used for model building is open source and has been added to this repository. Most packages used are usually pre-installed in most developed environments and tools like collab, jupyter, etc. This can be useful for people looking to enhance the way the code their predicitve models and efficient ways to deal with tabular data!

Style transfer between images was performed using the VGG19 model. The necessary codes, libraries and all other information of this project are available below

The purpose of this project is create a predictive model capable of identifying the probability of a person securing an admit based on their personal profile parameters. Simplified visualisations have been created for understanding the data. 80% accuracy was achieved on the test set.

Audio Source Separation is the process of separating a mixture into isolated sounds from individual sources (e.g. just the lead vocals).

Description This library provides an abstraction to perform Model Versioning using Weight & Biases. Features Version a new trained model Promote a mod

A cut down version of QUANT containing just the model in Python (QUANTPy)

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

GreaseLM: Graph REASoning Enhanced Language Models This repo provides the source code & data of our paper "GreaseLM: Graph REASoning Enhanced Language

EdiBERT, a generative model for image editing EdiBERT is a generative model based on a bi-directional transformer, suited for image manipulation. The

The current workflow simulates brain functional connectivity (FC) from structural connectivity (SC) with a neural mass model. Gradient descent is applied to optimize the parameters in the neural mass model.

RoNER RoNER is a Named Entity Recognition model based on a pre-trained BERT transformer model trained on RONECv2. It is meant to be an easy to use, hi