Python Data-efficient-learning Resources

A Novel Incremental Learning Driven Instance Segmentation Framework to Recognize Highly Cluttered Instances of the Contraband Items This repository co

EOD Easy and Efficient Object Detector EOD (Easy and Efficient Object Detection) is a general object detection model production framework. It aim on p

Introduction This code is the implementation of the paper "Coherence-Based Distributed Document Representation Learning for Scientific Documents". If

Plant extraction workflow Source code for the plant extraction workflow introduced in the paper "Agricultural Plant Cataloging and Establishment of a

FEMDA: Robust classification with Flexible Discriminant Analysis in heterogeneous data. Flexible EM-Inspired Discriminant Analysis is a robust supervised classification algorithm that performs well in noisy and contaminated datasets.

{ATAM} Active Transport Analytics Model Active Transport Analytics Model (“ATAM”

Historic Weather for Home Assistant (CC) 2022 by Andreas Frisch github@fraxinas.

Python-for-DS In this repo, I will put all the code related to data science using python libraries like Numpy, Pandas, Matplotlib, Seaborn and many mo

Data-Science-Intern-Challenge This repository contains answers of the Shopify Summer 2022 Data Science Intern Challenge. Summer 2022 Data Science Inte

{ATAM} Active Transport Analytics Model Active Transport Analytics Model (“ATAM”) is a new strategic transport modelling and data visualization framew

Validate arbitrary base64-encoded image uploads as incoming data urls while preserving image integrity but removing EXIF and unwanted artifacts and mitigating RCE-exploit potential.

This is a simple website crawler which asks for a website link from the user to crawl and find specific data from the given website address.

try_tf_serving ├───dataset │ ├───testing │ │ ├───paper │ │ ├───rock │ │ └───scissors │ └───training │ ├───paper │ ├───rock

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

GANfolk are AI-generated renderings of fictional people. Each image in the collection was created by a pair of Generative Adversarial Networks (GANs) with names and backstories also created with AI. The GANs were trained using portraits from artists like Renoir, Turner, and Modigliani in addition to open-source, modern photos.

DS2 Class 2022, Big Data & Cloud Computing for Oceanography Home of the 2022 ISblue Big Data & Cloud Computing for Oceanography class (IMT-A, ENSTA, I

MLOpsNameGenerator Overall Goal The goal of the project is to develop a model that is capable of creating Pokémon names based on its description, usin

Analyzing Skill Expression in Games This is a repo where I describe a method to measure the amount of skill expression games have. Table of Contents M

CTAB-GAN This is the official git paper CTAB-GAN: Effective Table Data Synthesizing. The paper is published on Asian Conference on Machine Learning (A

Reddit Data Collector Reddit Data Collector is a Python package that allows a user to collect post and comment data from Reddit. It is built on top of

Auto Label Pipeline A practical ML pipeline for data labeling with experiment tracking using DVC Goals: Demonstrate reproducible ML Use DVC to build a

Semi Intelligent BOT The project involves : Classifying fake news Classifying objects such as aeroplane, automobile, bird, cat, deer, dog, frog, horse

3D-Face-Modeling A vanilla 3D face modeling on pose-invariant and multi-lightning image data Table of Contents Background Install Usage Contributing B

An-Introduction-to-Statistical-Learning This repository contains the exercises and its solution contained in the book An Introduction to Statistical L

Deep Learning with TensorFlow 2 and Keras – Notebooks This project accompanies my Deep Learning with TensorFlow 2 and Keras trainings. It contains the

The Unsplash Dataset The Unsplash Dataset is made up of over 250,000+ contributing global photographers and data sourced from hundreds of millions of

A Machine Learning Course with Python Table of Contents Download Free Deep Learning Resource Guide Slack Group Introduction Motivation Machine Learnin

TensorLayer is a novel TensorFlow-based deep learning and reinforcement learning library designed for researchers and engineers. It provides an extens

Trax — Deep Learning with Clear Code and Speed Trax is an end-to-end library for deep learning that focuses on clear code and speed. It is actively us

Status: Maintenance (expect bug fixes and minor updates) Welcome to Spinning Up in Deep RL! This is an educational resource produced by OpenAI that ma

machine_learning_examples A collection of machine learning examples and tutorials.

Using Deep Q-Network to Learn How To Play Flappy Bird 7 mins version: DQN for flappy bird Overview This project follows the description of the Deep Q

深度学习在图像处理中的应用教程 前言 本教程是对本人研究生期间的研究内容进行整理总结，总结的同时也希望能够帮助更多的小伙伴。后期如果有学习到新的知识也会与大家一起分享。 本教程会以视频的方式进行分享，教学流程如下： 1）介绍网络的结构与创新点 2）使用Pytorch进行网络的搭建与训练 3）使用Te

Intro Real-time object detection and classification. Paper: version 1, version 2. Read more about YOLO (in darknet) and download weight files here. In

Great Expectations Always know what to expect from your data. Introduction Great Expectations helps data teams eliminate pipeline debt, through data t

NLP Best Practices In recent years, natural language processing (NLP) has seen quick growth in quality and usability, and this has helped to drive bus

DeepCTR DeepCTR is a Easy-to-use,Modular and Extendible package of deep-learning based CTR models along with lots of core components layers which can

Break The Ice With Python A journey of 100+ simple yet interesting problems which are explained, solved, discussed in different pythonic ways Introduc

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

Machine Learning University: Accelerated Natural Language Processing Class This repository contains slides, notebooks and datasets for the Machine Lea

Easy training on custom dataset. Various backends (MobileNet and SqueezeNet) supported. A YOLO demo to detect raccoon run entirely in brower is accessible at https://git.io/vF7vI (not on Windows).

The Deep Learning Book - Goodfellow, I., Bengio, Y., and Courville, A. (2016) This content is part of a series following the chapter 2 on linear algeb

Natural Language Processing with PyTorch Build Intelligent Language Applications Using Deep Learning By Delip Rao and Brian McMahan Welcome. This is a

NLP-Models-Tensorflow, Gathers machine learning and tensorflow deep learning models for NLP problems, code simplify inside Jupyter Notebooks 100%. Tab

100 pandas puzzles Puzzles notebook Solutions notebook Inspired by 100 Numpy exerises, here are 100* short puzzles for testing your knowledge of panda

🎉TensorFlow2.0-Examples🎉! "Talk is cheap, show me the code." ----- Linus Torvalds Created by YunYang1994 This tutorial was designed for easily divin

FMA: A Dataset For Music Analysis Michaël Defferrard, Kirell Benzi, Pierre Vandergheynst, Xavier Bresson. International Society for Music Information

Python for downloading model data (HRRR, RAP, GFS, NBM, etc.) from NOMADS, NOAA's Big Data Program partners (Amazon, Google, Microsoft), and the University of Utah Pando Archive System.

Minimal ML algorithms This repo includes minimal implementations of popular ML algorithms using pure python and numpy. The purpose of these notebooks

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

Predictive Modeling & Analytics on Home Equity Line of Credit Data (Python) HMEQ Data Set In this assignment we will use Python to examine a data set

Forex Data Prediction via Recurrent Neural Network Deep Sequence Modeling Research Paper Our research paper can be viewed here Installation Clone the

Fake news detection Implements a fake news detection program using classifiers for Data Mining course at UoA. Description The project is the categoriz

Data Structures and Algorithms: This is a collection of data structures and algorithms that I write while learning the subject Stack: stack.py A stack

MVS2D: Efficient Multi-view Stereo via Attention-Driven 2D Convolutions Project Page | Paper If you find our work useful for your research, please con

1 Meta-FDMIxup Repository for the paper : Meta-FDMixup: Cross-Domain Few-Shot Learning Guided byLabeled Target Data. (ACM MM 2021) paper News! the rep

Multi-Time Attention Networks (mTANs) This repository contains the PyTorch implementation for the paper Multi-Time Attention Networks for Irregularly

Fast Training of Neural Lumigraph Representations using Meta Learning Project Page | Paper | Data Alexander W. Bergman, Petr Kellnhofer, Gordon Wetzst

bizarre-pose-estimator Transfer Learning for Pose Estimation of Illustrated Characters Shuhong Chen *, Matthias Zwicker * WACV2022 [arxiv] [video] [po

Meta Learning Backpropagation And Improving It (VSML) This is research code for the NeurIPS 2021 publication Kirsch & Schmidhuber 2021. Many concepts

Satellite orbit height ◾ Requirements Python = 3.8 Packages listen in reuirements.txt (run pip install -r requirements.txt) Account on Space Track ◾

R3E Launch Tool A tool for RaceRoom Racing Experience which shows you launch data. Usage Run the tool, change the Stop Speed to whatever you want, and

Deals of the Day This is a web scraper, using the Python framework Scrapy, built to extract data such as price and product name from the Deals of the

mercury-db This is a File Based Key-Value Datastore that supports basic CRUD (Create, Read, Update, Delete) operations developed using Python. The dat

To attract customers, the hotel chain has added to its website the ability to book a room without prepayment. We need to predict whether the customer is going to reject the booking or not. Since in case of refusal, the hotel incurs losses.

BCI-ToolBox 1. Introduction BCI-ToolBox is deep learning pipeline for motor-imagery classification. This repo contains five models: ShallowConvNet, De

College-Prediction Project- Overview: Many have tried, many have failed. Few trailblazers are ambitious enought to chase acceptance into the top 15 un

Youtubist Basically fork of yt-dlp python module to my needs. You can paste playlist or channel link on the YouTube. It will automatically format to s

A Simple Neural Network from scratch A Simple Neural Network from scratch in Pyt

auto_code_complete is a auto word-completetion program which allows you to customize it on your needs. the model for this program is one of the deep-learning NLP(Natural Language Process) model structure called 'GRU(gated recurrent unit)'.

Fast ES-RNN: A GPU Implementation of the ES-RNN Algorithm A GPU-enabled version of the hybrid ES-RNN model by Slawek et al that won the M4 time-series

LSTM Neural Network for Time Series Prediction LSTM built using the Keras Python package to predict time series steps and sequences. Includes sine wav

List of Implementations: Currently, the reimplementation of the DeepAR paper(DeepAR: Probabilistic Forecasting with Autoregressive Recurrent Networks

Deep Learning for Time Series Classification As the simplest type of time series data, univariate time series provides a reasonably good starting poin

Machine-Learning-for-Time-Series-with-Python Become proficient in deriving insights from time-series data and analyzing a model’s performance Links Am

Deep Learning for Time Series Classification This is the companion repository for our paper titled "Deep learning for time series classification: a re

U-Time & U-Sleep Official implementation of The U-Time [1] model for general-purpose time-series segmentation. The U-Sleep [2] model for resilient hig

Multilabel time series classification with LSTM Tensorflow implementation of model discussed in the following paper: Learning to Diagnose with LSTM Re

Wearables Development Toolkit (WDK) The Wearables Development Toolkit (WDK) is a framework and set of tools to facilitate the iterative development of

DeltaPy⁠⁠ — Tabular Data Augmentation & Feature Engineering Finance Quant Machine Learning ML-Quant.com - Automated Research Repository Introduction T

tsaug tsaug is a Python package for time series augmentation. It offers a set of augmentation methods for time series, as well as a simple API to conn

Deep learning for time series forecasting Flow forecast is an open-source deep learning for time series forecasting framework. It provides all the lat

Supervised forecasting of sequential data in Python. Intro Supervised forecasting is the machine learning task of making predictions for sequential da

TIMEX TIMEX (referred in code as timexseries) is a framework for time-series-forecasting-as-a-service. Its main goal is to provide a simple and generi

shaplets Python implementation of the Learning Time-Series Shapelets method by Josif Grabocka et al., that learns a shapelet-based time-series classif

Overcoming-Catastrophic-forgetting-in-Neural-Networks Elastic weight consolidation technique for incremental learning. About Use this API if you dont

Alibi Detect is an open source Python library focused on outlier, adversarial and drift detection. The package aims to cover both online and offline d

AutoTS AutoTS is a time series package for Python designed for rapidly deploying high-accuracy forecasts at scale. There are dozens of forecasting mod

cesium: Open-Source Platform for Time Series Inference Summary cesium is an open source library that allows users to: extract features from raw time s

Gordo Building thousands of models with timeseries data to monitor systems. Table of content About Examples Install Uninstall Developer manual How to

What is survival analysis and why should I learn it? Survival analysis was originally developed and applied heavily by the actuarial and medical commu

Python Outlier Detection (PyOD) Deployment & Documentation & Stats & License PyOD is a comprehensive and scalable Python toolkit for detecting outlyin

🌄 Scalecast: Dynamic Forecasting at Scale About This package uses a scaleable forecasting approach in Python with common scikit-learn and statsmodels

scikit-hts Hierarchical Time Series with a familiar API. This is the result from not having found any good implementations of HTS on-line, and my work

"One of the holy grails of machine learning is to automate more and more of the feature engineering process." ― Pedro Domingos, A Few Useful Things to

Time Series Feature Extraction Library Intuitive time series feature extraction This repository hosts the TSFEL - Time Series Feature Extraction Libra

Turing Change Point Detection Benchmark Welcome to the repository for the Turing Change Point Detection Benchmark, a benchmark evaluation of change po

Khiva-Python Build Documentation Build Linux and Mac OS Build Windows Code Coverage README This is the Khiva Python binding, it allows the usage of Kh

=================================================== Nitime: timeseries analysis for neuroscience data ===============================================

WTTE-RNN Weibull Time To Event Recurrent Neural Network A less hacky machine-learning framework for churn- and time to event prediction. Forecasting p