7059 Repositories
Python data-uncertainty-learning Libraries
Apache Spark & Python (pySpark) tutorials for Big Data Analysis and Machine Learning as IPython / Jupyter notebooks
Spark Python Notebooks This is a collection of IPython notebook/Jupyter notebooks intended to train the reader on different Apache Spark concepts, fro
🤖 ⚡ scikit-learn tips
🤖 ⚡ scikit-learn tips New tips are posted on LinkedIn, Twitter, and Facebook. 👉 Sign up to receive 2 video tips by email every week! 👈 List of all
A series of Jupyter notebooks with Chinese comment that walk you through the fundamentals of Machine Learning and Deep Learning in python using Scikit-Learn and TensorFlow.
Hands-on-Machine-Learning 目的 这份笔记旨在帮助中文学习者以一种较快较系统的方式入门机器学习, 是在学习Hands-on Machine Learning with Scikit-Learn and TensorFlow这本书的 时候做的个人笔记: 此项目的可取之处 原书的
Introduction to Statistics and Basics of Mathematics for Data Science - The Hacker's Way
HackerMath for Machine Learning “Study hard what interests you the most in the most undisciplined, irreverent and original manner possible.” ― Richard
List of papers, code and experiments using deep learning for time series forecasting
Deep Learning Time Series Forecasting List of state of the art papers focus on deep learning and resources, code and experiments using deep learning f
Jupyter Notebook tutorials on solving real-world problems with Machine Learning & Deep Learning using PyTorch
Jupyter Notebook tutorials on solving real-world problems with Machine Learning & Deep Learning using PyTorch. Topics: Face detection with Detectron 2, Time Series anomaly detection with LSTM Autoencoders, Object Detection with YOLO v5, Build your first Neural Network, Time Series forecasting for Coronavirus daily cases, Sentiment Analysis with BERT.
Koç University deep learning framework.
Knet Knet (pronounced "kay-net") is the Koç University deep learning framework implemented in Julia by Deniz Yuret and collaborators. It supports GPU
Setup and customize deep learning environment in seconds.
Deepo is a series of Docker images that allows you to quickly set up your deep learning research environment supports almost all commonly used deep le
Hide screen when boss is approaching.
BossSensor Hide your screen when your boss is approaching. Demo The boss stands up. He is approaching. When he is approaching, the program fetches fac
Anomaly detection related books, papers, videos, and toolboxes
Anomaly Detection Learning Resources Outlier Detection (also known as Anomaly Detection) is an exciting yet challenging field, which aims to identify
Largest list of models for Core ML (for iOS 11+)
Since iOS 11, Apple released Core ML framework to help developers integrate machine learning models into applications. The official documentation We'v
Distributed deep learning on Hadoop and Spark clusters.
Note: we're lovingly marking this project as Archived since we're no longer supporting it. You are welcome to read the code and fork your own version
My solution to the book A Collection of Data Science Take-Home Challenges
DS-Take-Home Solution to the book "A Collection of Data Science Take-Home Challenges". Note: Please don't contact me for the dataset. This repository
Official PyTorch implementation of "Dual Path Learning for Domain Adaptation of Semantic Segmentation".
Dual Path Learning for Domain Adaptation of Semantic Segmentation Official PyTorch implementation of "Dual Path Learning for Domain Adaptation of Sema
Official re-implementation of the Calibrated Adversarial Refinement model described in the paper Calibrated Adversarial Refinement for Stochastic Semantic Segmentation
Official re-implementation of the Calibrated Adversarial Refinement model described in the paper Calibrated Adversarial Refinement for Stochastic Semantic Segmentation
Official repository for "Orthogonal Projection Loss" (ICCV'21)
Orthogonal Projection Loss (ICCV'21) Kanchana Ranasinghe, Muzammal Naseer, Munawar Hayat, Salman Khan, & Fahad Shahbaz Khan Paper Link | Project Page
Learning with Noisy Labels via Sparse Regularization, ICCV2021
Learning with Noisy Labels via Sparse Regularization This repository is the official implementation of [Learning with Noisy Labels via Sparse Regulari
Code for "Learning Skeletal Graph Neural Networks for Hard 3D Pose Estimation" ICCV'21
Skeletal-GNN Code for "Learning Skeletal Graph Neural Networks for Hard 3D Pose Estimation" ICCV'21 Various deep learning techniques have been propose
Implementation of Cross-category Video Highlight Detection via Set-based Learning (ICCV 2021).
Cross-category Video Highlight Detection via Set-based Learning Introduction This project is an implementation of ``Cross-category Video Highlight Det
Foreground-Action Consistency Network for Weakly Supervised Temporal Action Localization
FAC-Net Foreground-Action Consistency Network for Weakly Supervised Temporal Action Localization Linjiang Huang (CUHK), Liang Wang (CASIA), Hongsheng
Cleaned test data list of DukeMTMC-reID, ICCV2021
Cleaned DukeMTMC-reID Cleaned data list of DukeMTMC-reID released with our paper accepted by ICCV 2021: Learning Instance-level Spatial-Temporal Patte
Seasonal Contrast: Unsupervised Pre-Training from Uncurated Remote Sensing Data
Seasonal Contrast: Unsupervised Pre-Training from Uncurated Remote Sensing Data This is the official PyTorch implementation of the SeCo paper: @articl
Train Scene Graph Generation for Visual Genome and GQA in PyTorch = 1.2 with improved zero and few-shot generalization.
Scene Graph Generation Object Detections Ground truth Scene Graph Generated Scene Graph In this visualization, woman sitting on rock is a zero-shot tr
PyTorch implementation of paper "MT-ORL: Multi-Task Occlusion Relationship Learning" (ICCV 2021)
MT-ORL: Multi-Task Occlusion Relationship Learning Official implementation of paper "MT-ORL: Multi-Task Occlusion Relationship Learning" (ICCV 2021) P
Resco: A simple python package that report the effect of deep residual learning
resco Description resco is a simple python package that report the effect of dee
a curated list of docker-compose files prepared for testing data engineering tools, databases and open source libraries.
data-services A repository for storing various Data Engineering docker-compose files in one place. How to use it ? Set the required settings in .env f
Customer Service Requests Analysis is one of the practical life problems that an analyst may face. This Project is one such take. The project is a beginner to intermediate level project. This repository has a Source Code, README file, Dataset, Image and License file.
Customer Service Requests Analysis Project 1 DESCRIPTION Background of Problem Statement : NYC 311's mission is to provide the public with quick and e
deep learning model with only python and numpy with test accuracy 99 % on mnist dataset and different optimization choices
deep_nn_model_with_only_python_100%_test_accuracy deep learning model with only python and numpy with test accuracy 99 % on mnist dataset and differen
Creating a python package to convert /transfer excelsheet data to a mysql Database Table
Creating a python package to convert /transfer excelsheet data to a mysql Database Table
Code and Experiments for ACL-IJCNLP 2021 Paper Mind Your Outliers! Investigating the Negative Impact of Outliers on Active Learning for Visual Question Answering.
Code and Experiments for ACL-IJCNLP 2021 Paper Mind Your Outliers! Investigating the Negative Impact of Outliers on Active Learning for Visual Question Answering.
This is the code of paper ``Contrastive Coding for Active Learning under Class Distribution Mismatch'' with python.
Contrastive Coding for Active Learning under Class Distribution Mismatch Official PyTorch implementation of ["Contrastive Coding for Active Learning u
Source code for Task-Aware Variational Adversarial Active Learning
Task-Aware Variational Adversarial Active Learning - Official Pytorch implementation of the CVPR 2021 paper Kwanyoung Kim, Dongwon Park, Kwang In Kim,
Sequential GCN for Active Learning
Sequential GCN for Active Learning Please cite if using the code: Link to paper. Requirements: python 3.6+ torch 1.0+ pip libraries: tqdm, sklearn, sc
Code for the paper "Can Active Learning Preemptively Mitigate Fairness Issues?" presented at RAI 2021.
Can Active Learning Preemptively Mitigate Fairness Issues? Code for the paper "Can Active Learning Preemptively Mitigate Fairness Issues?" presented a
State-Relabeling Adversarial Active Learning
State-Relabeling Adversarial Active Learning Code for SRAAL [2020 CVPR Oral] Requirements torch = 1.6.0 numpy = 1.19.1 tqdm = 4.31.1 AL Results The
An implementation of the BADGE batch active learning algorithm.
Batch Active learning by Diverse Gradient Embeddings (BADGE) An implementation of the BADGE batch active learning algorithm. Details are provided in o
Code for the paper "Reinforced Active Learning for Image Segmentation"
Reinforced Active Learning for Image Segmentation (RALIS) Code for the paper Reinforced Active Learning for Image Segmentation Dependencies python 3.6
A curated list of awesome Active Learning
Awesome Active Learning 🤩 A curated list of awesome Active Learning ! 🤩 Background (image source: Settles, Burr) What is Active Learning? Active lea
python 93% acc. CNN Dogs Vs Cats ( Pytorch )
English | 简体中文(测试中...敬请期待) Cnn-Classification-Dog-Vs-Cat 猫狗辨别 (pytorch版本) CNN Resnet18 的猫狗分类器,基于ResNet及其变体网路系列,对于一般的图像识别任务表现优异,模型精准度高达93%(小型样本)。 项目制作于
Lol qq parser - A League of Legends parser for QQ data
lol_qq_parser A League of Legends parser for QQ data Sources This package relies
A library for graph deep learning research
Documentation | Paper [JMLR] | Tutorials | Benchmarks | Examples DIG: Dive into Graphs is a turnkey library for graph deep learning research. Why DIG?
Python bindings for Basler's VisualApplets TCL script generation
About visualapplets.py The Basler AG company provides a TCL scripting engine to automatize the creation of VisualApplets designs (a former Silicon Sof
Maiden & Spell community player ranking based on tournament data.
MnSRank Maiden & Spell community player ranking based on tournament data. Why? 2021 just ended and this seemed like a cool idea. Elo doesn't work well
A Telegram crawler to search groups and channels automatically and collect any type of data from them.
Introduction This is a crawler I wrote in Python using the APIs of Telethon months ago. This tool was not intended to be publicly available for a numb
Predico Disease Prediction system based on symptoms provided by patient- using Python-Django & Machine Learning
Predico Disease Prediction system based on symptoms provided by patient- using Python-Django & Machine Learning
NewpaperNews-API - Json data of the news with python
NewsAPI API Documentation BASE_URL = "https://saurav.tech/NewsAPI/" top_headline
A part of HyRiver software stack for handling geospatial data manipulations
Package Description Status PyNHD Navigate and subset NHDPlus (MR and HR) using web services Py3DEP Access topographic data through National Map's 3DEP
MNE: Magnetoencephalography (MEG) and Electroencephalography (EEG) in Python
MNE-Python MNE-Python software is an open-source Python package for exploring, visualizing, and analyzing human neurophysiological data such as MEG, E
PyExplainer: A Local Rule-Based Model-Agnostic Technique (Explainable AI)
PyExplainer PyExplainer is a local rule-based model-agnostic technique for generating explanations (i.e., why a commit is predicted as defective) of J
The module that allows the collection of data sampling, which is transmitted with WebSocket via WIFI or serial port for CSV file.
The module that allows the collection of data sampling, which is transmitted with WebSocket via WIFI or serial port for CSV file.
Uproot is a library for reading and writing ROOT files in pure Python and NumPy.
Uproot is a library for reading and writing ROOT files in pure Python and NumPy. Unlike the standard C++ ROOT implementation, Uproot is only an I/O li
Simulate genealogical trees and genomic sequence data using population genetic models
msprime msprime is a population genetics simulator based on tskit. Msprime can simulate random ancestral histories for a sample of individuals (consis
make ASCII Art by Deep Learning
DeepAA This is convolutional neural networks generating ASCII art. This repository is under construction. This work is accepted by NIPS 2017 Workshop,
PyMove is a Python library to simplify queries and visualization of trajectories and other spatial-temporal data
Use PyMove and go much further Information Package Status License Python Version Platforms Build Status PyPi version PyPi Downloads Conda version Cond
Python Client for Algorithmia Algorithms and Data API
Algorithmia Common Library (python) Python client library for accessing the Algorithmia API For API documentation, see the PythonDocs Algorithm Develo
constructing maps of intellectual influence from publication data
Influencemap Project @ ANU Influence in the academic communities has been an area of interest for researchers. This can be seen in the popularity of a
Forum written for learning purposes in flask and sqlalchemy
Flask-forum forum written for learning purposes using SQLalchemy and flask How to install install requirements pip install sqlalchemy flask clone repo
Python client for using Prefect Cloud with Saturn Cloud
prefect-saturn prefect-saturn is a Python package that makes it easy to run Prefect Cloud flows on a Dask cluster with Saturn Cloud. For a detailed tu
A Python Package For System Identification Using NARMAX Models
SysIdentPy is a Python module for System Identification using NARMAX models built on top of numpy and is distributed under the 3-Clause BSD license. N
BigDL - Evaluate the performance of BigDL (Distributed Deep Learning on Apache Spark) in big data analysis problems
Evaluate the performance of BigDL (Distributed Deep Learning on Apache Spark) in big data analysis problems.
Machine Learning Study 혼자 해보기
Machine Learning Study 혼자 해보기 기여자 (Contributors) ✨ Teddy Lee 🏠 HongJaeKwon 🏠 Seungwoo Han 🏠 Tae Heon Kim 🏠 Steve Kwon 🏠 SW Song 🏠 K1A2 🏠 Wooil
Code repo for the book "Feature Engineering for Machine Learning," by Alice Zheng and Amanda Casari, O'Reilly 2018
feature-engineering-book This repo accompanies "Feature Engineering for Machine Learning," by Alice Zheng and Amanda Casari. O'Reilly, 2018. The repo
Advbox is a toolbox to generate adversarial examples that fool neural networks in PaddlePaddle、PyTorch、Caffe2、MxNet、Keras、TensorFlow and Advbox can benchmark the robustness of machine learning models.
Advbox is a toolbox to generate adversarial examples that fool neural networks in PaddlePaddle、PyTorch、Caffe2、MxNet、Keras、TensorFlow and Advbox can benchmark the robustness of machine learning models. Advbox give a command line tool to generate adversarial examples with Zero-Coding.
Official Repsoitory for "Mish: A Self Regularized Non-Monotonic Neural Activation Function" [BMVC 2020]
Mish: Self Regularized Non-Monotonic Activation Function BMVC 2020 (Official Paper) Notes: (Click to expand) A considerably faster version based on CU
Rainbow is all you need! A step-by-step tutorial from DQN to Rainbow
Do you want a RL agent nicely moving on Atari? Rainbow is all you need! This is a step-by-step tutorial from DQN to Rainbow. Every chapter contains bo
Machine Learning in Asset Management (by @firmai)
Machine Learning in Asset Management If you like this type of content then visit ML Quant site below: https://www.ml-quant.com/ Part One Follow this l
Pytorch implementations of Bayes By Backprop, MC Dropout, SGLD, the Local Reparametrization Trick, KF-Laplace, SG-HMC and more
Bayesian Neural Networks Pytorch implementations for the following approximate inference methods: Bayes by Backprop Bayes by Backprop + Local Reparame
The official code repository for examples in the O'Reilly book 'Generative Deep Learning'
Generative Deep Learning Teaching Machines to paint, write, compose and play The official code repository for examples in the O'Reilly book 'Generativ
Machine Learning University: Accelerated Computer Vision Class
Machine Learning University: Accelerated Computer Vision Class This repository contains slides, notebooks, and datasets for the Machine Learning Unive
Algorithms written in different programming languages
Data Structures and Algorithms Clean example implementations of data structures and algorithms written in different languages. List of implementations
Face Mask Detection system based on computer vision and deep learning using OpenCV and Tensorflow/Keras
Face Mask Detection Face Mask Detection System built with OpenCV, Keras/TensorFlow using Deep Learning and Computer Vision concepts in order to detect
Keras implementation of "One pixel attack for fooling deep neural networks" using differential evolution on Cifar10 and ImageNet
One Pixel Attack How simple is it to cause a deep neural network to misclassify an image if an attacker is only allowed to modify the color of one pix
🏖 Keras Implementation of Painting outside the box
Keras implementation of Image OutPainting This is an implementation of Painting Outside the Box: Image Outpainting paper from Standford University. So
Vehicle detection using machine learning and computer vision techniques for Udacity's Self-Driving Car Engineer Nanodegree.
Vehicle Detection Video demo Overview Vehicle detection using these machine learning and computer vision techniques. Linear SVM HOG(Histogram of Orien
Quilt is a self-organizing data hub for S3
Quilt is a self-organizing data hub Python Quick start, tutorials If you have Python and an S3 bucket, you're ready to create versioned datasets with
DL course co-developed by YSDA, HSE and Skoltech
Deep learning course This repo supplements Deep Learning course taught at YSDA and HSE @fall'21. For previous iteration visit the spring21 branch. Lec
Full Stack Deep Learning Labs
Full Stack Deep Learning Labs Welcome! Project developed during lab sessions of the Full Stack Deep Learning Bootcamp. We will build a handwriting rec
Implementations of CNNs, RNNs, GANs, etc
Tensorflow Programs and Tutorials This repository will contain Tensorflow tutorials on a lot of the most popular deep learning concepts. It'll also co
This repository contains small projects related to Neural Networks and Deep Learning in general.
ILearnDeepLearning.py Description People say that nothing develops and teaches you like getting your hands dirty. This repository contains small proje
A collection of Reinforcement Learning algorithms from Sutton and Barto's book and other research papers implemented in Python.
Reinforcement-Learning-Notebooks A collection of Reinforcement Learning algorithms from Sutton and Barto's book and other research papers implemented
NeuralTalk is a Python+numpy project for learning Multimodal Recurrent Neural Networks that describe images with sentences.
#NeuralTalk Warning: Deprecated. Hi there, this code is now quite old and inefficient, and now deprecated. I am leaving it on Github for educational p
This is a Tensorflow implementation of Learning to See in the Dark in CVPR 2018
Learning-to-See-in-the-Dark This is a Tensorflow implementation of Learning to See in the Dark in CVPR 2018, by Chen Chen, Qifeng Chen, Jia Xu, and Vl
A next-generation curated knowledge sharing platform for data scientists and other technical professions.
Knowledge Repo The Knowledge Repo project is focused on facilitating the sharing of knowledge between data scientists and other technical roles using
Data on COVID-19 (coronavirus) cases, deaths, hospitalizations, tests • All countries • Updated daily by Our World in Data
COVID-19 Dataset by Our World in Data Find our data on COVID-19 and its documentation in public/data. Documentation Data: complete COVID-19 dataset Da
A distributed crawler for weibo, building with celery and requests.
A distributed crawler for weibo, building with celery and requests.
TensorFlow implementation of AlexNet and its training and testing on ImageNet ILSVRC 2012 dataset
AlexNet training on ImageNet LSVRC 2012 This repository contains an implementation of AlexNet convolutional neural network and its training and testin
Sistema de tratamento e análise de grandes volumes de dados através de técnicas de Data Science
Sistema de tratamento e análise de grandes volumes de dados através de técnicas de data science Todos os scripts, gráficos e relatórios de todas as at
IRON Kaggle project done while doing IRONHACK Bootcamp where we had to analyze and use a Machine Learning Project to predict future sales
IRON Kaggle project done while doing IRONHACK Bootcamp where we had to analyze and use a Machine Learning Project to predict future sales. In this case, we ended up using XGBoost because it was the one with a higher score and less overfitting.
Bunch of different tools which helps visualizing and annotating images for semantic/instance segmentation tasks
Data Framework for Semantic/Instance Segmentation Bunch of different tools which helps visualizing, transforming and annotating images for semantic/in
Code for NeurIPS 2021 paper: Invariant Causal Imitation Learning for Generalizable Policies
Invariant Causal Imitation Learning for Generalizable Policies Ioana Bica, Daniel Jarrett, Mihaela van der Schaar Neural Information Processing System
DeepLearning Anomalies Detection with Bluetooth Sensor Data
Final Year Project. Constructing models to create offline anomalies detection using Travel Time Data collected from Bluetooth sensors along the route.
It is a Blender Tool which can convert the Object Data Attributes in face corner to the UVs or Vertex Color.
Blender_ObjectDataAttributesConvertTool It is a Blender Tool which can convert the Object Data Attributes in face corner to the UVs or Vertex Color. D
An AI made using artificial intelligence (AI) and machine learning algorithms (ML) .
DTech.AIML An AI made using artificial intelligence (AI) and machine learning algorithms (ML) . This is created by help of some members in my team and
Crunchdao - Python API for the Crunchdao machine learning tournament
Python API for the Crunchdao machine learning tournament Interact with the Crunc
An interactive DNN Model deployed on web that predicts the chance of heart failure for a patient with an accuracy of 98%
Heart Failure Predictor About A Web UI deployed Dense Neural Network Model Made using Tensorflow that predicts whether the patient is healthy or has c
K-Means Clustering and Hierarchical Clustering Unsupervised Learning Solution in Python3.
Unsupervised Learning - K-Means Clustering and Hierarchical Clustering - The Heritage Foundation's Economic Freedom Index Analysis 2019 - By David Sal
Data cleaning, missing value handle, EDA use in this project
Lending Club Case Study Project Brief Solving this assignment will give you an idea about how real business problems are solved using EDA. In this cas
schemasheets - structuring your data using spreadsheets
schemasheets - structuring your data using spreadsheets Create a data dictionary / schema for your data using simple spreadsheets - no coding required
Code for paper "Multi-level Disentanglement Graph Neural Network"
Multi-level Disentanglement Graph Neural Network (MD-GNN) This is a PyTorch implementation of the MD-GNN, and the code includes the following modules:
Data and analysis code for an MS on SK VOC genomes phenotyping/neutralisation assays
Description Summary of phylogenomic methods and analyses used in "Immunogenicity of convalescent and vaccinated sera against clinical isolates of ance