Python Data-efficient-learning Resources

Element selection for functional materials discovery by integrated machine learning of atomic contributions to properties 8.11.2021 Andrij Vasylenko I

Image-based Navigation in Real-World Environments via Multiple Mid-level Representations: Fusion Models Benchmark and Efficient Evaluation This reposi

CausIL A repo for Causal Imitation Learning under Temporally Correlated Noise. Running Experiments To re-train an expert, run: python experts/train_ex

CodeContests CodeContests is a competitive programming dataset for machine-learning. This dataset was used when training AlphaCode. It consists of pro

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

LocUNet LocUNet is a deep learning method to localize a UE based solely on the reported signal strengths from a set of BSs. The method utilizes accura

Learning-based Camera Calibration A Learning-based Camera Calibration Toolbox Paper The pdf file can be found here. @misc{zhang2022learningbased,

Politics and Virality in the Time of Twitter Data and code accompanying the paper Politics and Virality in the Time of Twitter. In specific: the code

FewBit FewBit — a library for memory efficient training of large neural networks. Its efficiency originates from storage optimizations applied to back

ES_OTN_Public Carlos Güemes Palau, Paul Almasan, Pere Barlet Ros, Albert Cabellos Aparicio Contact us: [email protected], contactus@bn

Evolve plastic networks to be able to automatically acquire novel cognitive (meta-learning) tasks

Image data augmentation is a technique that can be used to artificially expand the size of a training dataset by creating modified versions of images in the dataset.

Data-Augmentation-Using-Keras-and-Python Data augmentation is the process of increasing the number of training dataset. Keras library offers a simple

Definitive Guide to Creating a SQL Database on Cloud with AWS and Python An easy-to-follow comprehensive guide on integrating Amazon RDS, MySQL Workbe

py-self-organizing-map Simple implementation of Self Organizing Maps (SOMs) with rectangular and hexagonal grid topologies. A SOM is a simple unsuperv

Structured Data Gradient Pruning (SDGP) Weight pruning is a technique to make Deep Neural Network (DNN) inference more computationally efficient by re

LinkScope Client Description This is the repository for the LinkScope Client Online Investigation software. LinkScope allows you to perform online inv

TailCalibX : Feature Generation for Long-tail Classification by Rahul Vigneswaran, Marc T. Law, Vineeth N. Balasubramanian, Makarand Tapaswi [arXiv] [

MinkLoc++: Lidar and Monocular Image Fusion for Place Recognition Paper: MinkLoc++: Lidar and Monocular Image Fusion for Place Recognition accepted fo

DiffStride is a pooling layer with learnable strides. Unlike strided convolutions, average pooling or max-pooling that require cross-validating stride values at each layer, DiffStride can be initialized with an arbitrary value at each layer (e.g. (2, 2) and during training its strides will be optimized for the task at hand.

This is the official repository of the paper: ElasticFace: Elastic Margin Loss for Deep Face Recognition Paper on arxiv: arxiv Model Log file Pretrain

Recommender systems are the systems that are designed to recommend things to the user based on many different factors. The recommender system deals with a large volume of information present by filtering the most important information based on the data provided by a user and other factors that take care of the user’s preference and interest.

An Efficient Library for Training Deep Models This repository provides an efficient PyTorch-based library for training deep models. Installation Make

A collection of algorithms and datastructures introduced during UoE's Introduction to Datastructures and Algorithms class.

chess-exporter Prometheus exporter for chess.com player data implemented via chess.com's published data API and Prometheus Python Client Example use c

Kartothek - a Python library to manage (create, read, update, delete) large amounts of tabular data in a blob store

Hybrid Machine learning Model Clone the Repository Create a new Directory as assests and download the model from the below link Model Link To Start th

APSIPA-TER This code is the implementation of Text Emotion Recognition (TER) with linguistic features. The network model is BERT with a pretrained mod

scdlpicker SeisComP/SeisBench interface to enable deep-learning (re)picking in SeisComP Objective This is a simple deep learning (DL) repicker module

APSIPA-SER-with-A-and-T This code is the implementation of Speech Emotion Recognition (SER) with acoustic and linguistic features. The network model i

sql2diagram Generate database table diagram from SQL data definition. e.g. "CREATE TABLE ..." See Example below How does it works? Analyze the SQL to

PATC: Introduction to Big Data Analytics. Practical Data Analytics for Solving Real World Problems

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.

MidTerm Project for the Data Analysis FT Bootcamp, Adam Tycner and Florent ZAHOUI Hallo

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

This repo contains the source code for crawler and crawled data of cars specifications from autodata. The data has roughly 45k cars

Python command line tool and python engine to label table fields and fields in data files. It could help to find meaningful data in your tables and data files or to find Personal identifable information (PII).

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

COVID19-WEB-SCRAPER Open Source Tech Lab - Project [SEMESTER IV] OSTL Assignments OSTL Assignments - 1 OSTL Assignments - 2 Project COVID19 India Data

strava_py Create artistic visualisations with your exercise data (Python version). This is a port of the R strava package to Python. Examples Facets A

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

Intro-to-Data-Science Conducted ANOVA and Logistic regression analysis. Project ANOVA The main aim of this project is to perform One-Way ANOVA analysi

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

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.

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

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

⚡️ Pokéhandy – Pokémon Hand Simulator [WIP 🚧 ] This application aims to simulat

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

InverterApi - This project has been designed to take monitoring data from Voltronic, Axpert, Mppsolar PIP, Voltacon, Effekta

Weather Image Recognition - Python weather application using series of data

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

Analysis of a dataset of 10000 passwords to find common trends and mistakes people generally make while setting up a password.

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.

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.

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 is intended to implement a solution designed to extract, transform and load Chicago crime data from an RDS instance to other services in AWS.

ADB IP ROTATE This an Python script based on Android Debug Bridge (adb) shell sc

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

MetaFrame A data structure that extends pyspark.sql.DataFrame with metadata info

sfgp is a package that aggregates individual scripts and notebooks, primarily written for the basic analysis tasks of genetics and pharmacogenomics data.

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

mapa 🌍 Create 3d-printable STLs from satellite elevation data Installation pip install mapa Usage mapa uses numpy and numba under the hood to crunch

SoccerData is a collection of wrappers over soccer data from Club Elo, ESPN, FBr

Automating reinforcement learning architecture design for code optimization. Che

Data from "Datamodels: Predicting Predictions with Training Data" Here we provid

Welcome! This readme will guide you through the use of the code in this reposito

ADE20k Semantic segmentation with MAE Getting started Install the mmsegmentation

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

catalogue_data Scripts to prepare catalogue data. Setup Clone this repo. Install

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

university-courses Python/Selenium script to scrape data about university courses. Script first extracts URLs of each courses homepage, then trawls ea

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

gpv2-web10k This repository contains the script to download images from the Web-10K dataset. The script takes in a list of queries, queries Bing Image

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

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

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

Common Voice Utils This repository collects together basic linguistic processing data for using dataset dumps from the Common Voice project. It aims t

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:

Hatchet Hatchet is a Python-based library that allows Pandas dataframes to be indexed by structured tree and graph data. It is intended for analyzing