5517 Repositories
Python coursera-machine-learning-engineering-for-prod-mlops-specialization Libraries
Automated Melanoma Recognition in Dermoscopy Images via Very Deep Residual Networks
Introduction This repository contains the modified caffe library and network architectures for our paper "Automated Melanoma Recognition in Dermoscopy
A boosting-based Multiple Instance Learning (MIL) package that includes MIL-Boost and MCIL-Boost
A boosting-based Multiple Instance Learning (MIL) package that includes MIL-Boost and MCIL-Boost
Repository features UNet inspired architecture used for segmenting lungs on chest X-Ray images
Lung Segmentation (2D) Repository features UNet inspired architecture used for segmenting lungs on chest X-Ray images. Demo See the application of the
Pre-trained models for a Cascaded-FCN in caffe and tensorflow that segments
Cascaded-FCN This repository contains the pre-trained models for a Cascaded-FCN in caffe and tensorflow that segments the liver and its lesions out of
Deep Learning to Improve Breast Cancer Detection on Screening Mammography
Shield: This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. Deep Learning to Improve Breast
Here we present the implementation in TensorFlow of our work about liver lesion segmentation accepted in the Machine Learning 4 Health Workshop
Detection-aided liver lesion segmentation Here we present the implementation in TensorFlow of our work about liver lesion segmentation accepted in the
This is a curated list of medical data for machine learning
Medical Data for Machine Learning This is a curated list of medical data for machine learning. This list is provided for informational purposes only,
Band-Adaptive Spectral-Spatial Feature Learning Neural Network for Hyperspectral Image Classification
Band-Adaptive Spectral-Spatial Feature Learning Neural Network for Hyperspectral Image Classification
Raster Vision is an open source Python framework for building computer vision models on satellite, aerial, and other large imagery sets
Raster Vision is an open source Python framework for building computer vision models on satellite, aerial, and other large imagery sets (including obl
This repository contains code, network definitions and pre-trained models for working on remote sensing images using deep learning
Deep learning for Earth Observation This repository contains code, network definitions and pre-trained models for working on remote sensing images usi
Generic ecosystem for feature extraction from aerial and satellite imagery
Note: Robosat is neither maintained not actively developed any longer by Mapbox. See this issue. The main developers (@daniel-j-h, @bkowshik) are no l
🛰️ Awesome Satellite Imagery Datasets
Awesome Satellite Imagery Datasets List of aerial and satellite imagery datasets with annotations for computer vision and deep learning. Newest datase
Learning to Segment Instances in Videos with Spatial Propagation Network
Learning to Segment Instances in Videos with Spatial Propagation Network This paper is available at the 2017 DAVIS Challenge website. Check our result
Source code of all the projects of Udacity Self-Driving Car Engineer Nanodegree.
self-driving-car In this repository I will share the source code of all the projects of Udacity Self-Driving Car Engineer Nanodegree. Hope this might
My capstone project for Udacity's Machine Learning Nanodegree
MLND-Capstone My capstone project for Udacity's Machine Learning Nanodegree Lane Detection with Deep Learning In this project, I use a deep learning-b
This is a Keras-based Python implementation of DeepMask- a complex deep neural network for learning object segmentation masks
NNProject - DeepMask This is a Keras-based Python implementation of DeepMask- a complex deep neural network for learning object segmentation masks. Th
Seg-Torch for Image Segmentation with Torch
Seg-Torch for Image Segmentation with Torch This work was sparked by my personal research on simple segmentation methods based on deep learning. It is
This implements the learning and inference/proposal algorithm described in "Learning to Propose Objects, Krähenbühl and Koltun"
Learning to propose objects This implements the learning and inference/proposal algorithm described in "Learning to Propose Objects, Krähenbühl and Ko
CN24 is a complete semantic segmentation framework using fully convolutional networks
Build status: master (production branch): develop (development branch): Welcome to the CN24 GitHub repository! CN24 is a complete semantic segmentatio
Segment axon and myelin from microscopy data using deep learning
Segment axon and myelin from microscopy data using deep learning. Written in Python. Using the TensorFlow framework. Based on a convolutional neural network architecture. Pixels are classified as either axon, myelin or background.
Taking A Closer Look at Domain Shift: Category-level Adversaries for Semantics Consistent Domain Adaptation
Taking A Closer Look at Domain Shift: Category-level Adversaries for Semantics Consistent Domain Adaptation (CVPR2019) This is a pytorch implementatio
DeepCO3: Deep Instance Co-segmentation by Co-peak Search and Co-saliency
[CVPR19] DeepCO3: Deep Instance Co-segmentation by Co-peak Search and Co-saliency (Oral paper) Authors: Kuang-Jui Hsu, Yen-Yu Lin, Yung-Yu Chuang PDF:
Natural Posterior Network: Deep Bayesian Predictive Uncertainty for Exponential Family Distributions
Natural Posterior Network This repository provides the official implementation o
Built a deep neural network (DNN) that functions as an end-to-end machine translation pipeline
Built a deep neural network (DNN) that functions as an end-to-end machine translation pipeline. The pipeline accepts english text as input and returns the French translation.
Machine-Learning with python (jupyter)
Machine-Learning with python (jupyter) 머신러닝 야학 작심 10일과 쥬피터 노트북 기반 데이터 사이언스 시작 들어가기전 https://nbviewer.org/ 페이지를 통해서 쥬피터 노트북 내용을 볼 수 있다. 위 페이지에서 현재 레포 기
Laporan Proyek Machine Learning - Azhar Rizki Zulma
Laporan Proyek Machine Learning - Azhar Rizki Zulma Project Overview Domain proyek yang dipilih dalam proyek machine learning ini adalah mengenai hibu
DTCN SMP Challenge - Sequential prediction learning framework and algorithm
DTCN This is the implementation of our paper "Sequential Prediction of Social Me
ESGD-M - A stochastic non-convex second order optimizer, suitable for training deep learning models, for PyTorch
ESGD-M - A stochastic non-convex second order optimizer, suitable for training deep learning models, for PyTorch
Video-Captioning - A machine Learning project to generate captions for video frames indicating the relationship between the objects in the video
Video-Captioning - A machine Learning project to generate captions for video frames indicating the relationship between the objects in the video
Personal Finance Forecaster - An AI tool for forecasting personal expenses
Personal Finance Forecaster - An AI tool for forecasting personal expenses
Synthetic data need to preserve the statistical properties of real data in terms of their individual behavior and (inter-)dependences
Synthetic data need to preserve the statistical properties of real data in terms of their individual behavior and (inter-)dependences. Copula and functional Principle Component Analysis (fPCA) are statistical models that allow these properties to be simulated (Joe 2014). As such, copula generated data have shown potential to improve the generalization of machine learning (ML) emulators (Meyer et al. 2021) or anonymize real-data datasets (Patki et al. 2016).
An easy-to-use feature store
A feature store is a data storage system for data science and machine-learning. It can store raw data and also transformed features, which can be fed straight into an ML model or training script.
This repository contains FEDOT - an open-source framework for automated modeling and machine learning (AutoML)
package tests docs license stats support This repository contains FEDOT - an open-source framework for automated modeling and machine learning (AutoML
Optuna is an automatic hyperparameter optimization software framework, particularly designed for machine learning
Optuna is an automatic hyperparameter optimization software framework, particularly designed for machine learning. It features an imperative, define-by-run style user API.
ParaMonte is a serial/parallel library of Monte Carlo routines for sampling mathematical objective functions of arbitrary-dimensions
ParaMonte is a serial/parallel library of Monte Carlo routines for sampling mathematical objective functions of arbitrary-dimensions, in particular, the posterior distributions of Bayesian models in data science, Machine Learning, and scientific inference, with the design goal of unifying the automation (of Monte Carlo simulations), user-friendliness (of the library), accessibility (from multiple programming environments), high-performance (at runtime), and scalability (across many parallel processors).
visualize_ML is a python package made to visualize some of the steps involved while dealing with a Machine Learning problem
visualize_ML visualize_ML is a python package made to visualize some of the steps involved while dealing with a Machine Learning problem. It is build
Real life contra a deep learning project built using mediapipe and openc
real-life-contra Description A python script that translates the body movement into in game control. Welcome to all new real life contra a deep learni
Solution to the first stage Quiz of Hamoye internship: Introduction to Python for Machine Learning
Author Ayanwoye, Gideon Ayandele - [email protected] SOLUTION TO HAMOYE STAGE A QUIZ INTRODUCTION TO PYTHON FOR MACHINE LEARNING The dataset is prov
HistoSeg : Quick attention with multi-loss function for multi-structure segmentation in digital histology images
HistoSeg : Quick attention with multi-loss function for multi-structure segmentation in digital histology images Histological Image Segmentation This
An experiment on the performance of homemade Q-learning AIs in Agar.io depending on their state representation and available actions
Agar.io_Q-Learning_AI An experiment on the performance of homemade Q-learning AIs in Agar.io depending on their state representation and available act
Feature engineering and machine learning: together at last
Feature engineering and machine learning: together at last! Lambdo is a workflow engine which significantly simplifies data analysis by unifying featu
This is a learning tool and exploration app made using the Dash interactive Python framework developed by Plotly
Support Vector Machine (SVM) Explorer This app has been moved here. This repo is likely outdated and will not be updated. This is a learning tool and
Tutorials, examples, collections, and everything else that falls into the categories: pattern classification, machine learning, and data mining
**Tutorials, examples, collections, and everything else that falls into the categories: pattern classification, machine learning, and data mining.** S
scikit-learn is a python module for machine learning built on top of numpy / scipy
About scikit-learn is a python module for machine learning built on top of numpy / scipy. The purpose of the scikit-learn-tutorial subproject is to le
Sentiment Classification using WSD, Maximum Entropy & Naive Bayes Classifiers
Sentiment Classification using WSD, Maximum Entropy & Naive Bayes Classifiers
This repository contains several jupyter notebooks to help users learn to use neon, our deep learning framework
neon_course This repository contains several jupyter notebooks to help users learn to use neon, our deep learning framework. For more information, see
Climin is a Python package for optimization, heavily biased to machine learning scenarios
climin climin is a Python package for optimization, heavily biased to machine learning scenarios distributed under the BSD 3-clause license. It works
Dive into Machine Learning
Dive into Machine Learning Hi there! You might find this guide helpful if: You know Python or you're learning it 🐍 You're new to Machine Learning You
TensorDebugger (TDB) is a visual debugger for deep learning. It extends TensorFlow with breakpoints + real-time visualization of the data flowing through the computational graph
TensorDebugger (TDB) is a visual debugger for deep learning. It extends TensorFlow (Google's Deep Learning framework) with breakpoints + real-time visualization of the data flowing through the computational graph.
Machine Learning for RC Cars
Suiron Machine Learning for RC Cars Prediction visualization (green = actual, blue = prediction) Click the video below to see it in action! Dependenci
Jupyter notebooks for the book "The Elements of Statistical Learning".
This repository contains Jupyter notebooks implementing the algorithms found in the book and summary of the textbook.
Neuron class provides LNU (Linear Neural Unit), QNU (Quadratic Neural Unit), RBF (Radial Basis Function), MLP (Multi Layer Perceptron), MLP-ELM (Multi Layer Perceptron - Extreme Learning Machine) neurons learned with Gradient descent or LeLevenberg–Marquardt algorithm
Neuron class provides LNU (Linear Neural Unit), QNU (Quadratic Neural Unit), RBF (Radial Basis Function), MLP (Multi Layer Perceptron), MLP-ELM (Multi Layer Perceptron - Extreme Learning Machine) neurons learned with Gradient descent or LeLevenberg–Marquardt algorithm
Demonstrate the breadth and depth of your data science skills by earning all of the Databricks Data Scientist credentials
Data Scientist Learning Plan Demonstrate the breadth and depth of your data science skills by earning all of the Databricks Data Scientist credentials
This is an open solution to the Home Credit Default Risk challenge 🏡
Home Credit Default Risk: Open Solution This is an open solution to the Home Credit Default Risk challenge 🏡 . More competitions 🎇 Check collection
Peek-a-Boo: What (More) is Disguised in a Randomly Weighted Neural Network, and How to Find It Efficiently
Peek-a-Boo: What (More) is Disguised in a Randomly Weighted Neural Network, and How to Find It Efficiently This repository is the official implementat
Google AI Open Images - Object Detection Track: Open Solution
Google AI Open Images - Object Detection Track: Open Solution This is an open solution to the Google AI Open Images - Object Detection Track 😃 More c
TGS Salt Identification Challenge
TGS Salt Identification Challenge This is an open solution to the TGS Salt Identification Challenge. Note Unfortunately, we can no longer provide supp
Airbus Ship Detection Challenge
Airbus Ship Detection Challenge This is an open solution to the Airbus Ship Detection Challenge. Our goals We are building entirely open solution to t
Bookmarkarchiver - Python script that archives all of your bookmarks on the Internet Archive
bookmarkarchiver Python script that archives all of your bookmarks on the Internet Archive. Supports all major browsers. bookmarkarchiver uses the off
PyToch implementation of A Novel Self-supervised Learning Task Designed for Anomaly Segmentation
Self-Supervised Anomaly Segmentation Intorduction This is a PyToch implementation of A Novel Self-supervised Learning Task Designed for Anomaly Segmen
Image Classification - A research on image classification and auto insurance claim prediction, a systematic experiments on modeling techniques and approaches
A research on image classification and auto insurance claim prediction, a systematic experiments on modeling techniques and approaches
Deep Learning: Architectures & Methods Project: Deep Learning for Audio Super-Resolution
Deep Learning: Architectures & Methods Project: Deep Learning for Audio Super-Resolution Figure: Example visualization of the method and baseline as a
Official implementation for "Symbolic Learning to Optimize: Towards Interpretability and Scalability"
Symbolic Learning to Optimize This is the official implementation for ICLR-2022 paper "Symbolic Learning to Optimize: Towards Interpretability and Sca
Open solution to the Toxic Comment Classification Challenge
Starter code: Kaggle Toxic Comment Classification Challenge More competitions 🎇 Check collection of public projects 🎁 , where you can find multiple
Language Models as Zero-Shot Planners: Extracting Actionable Knowledge for Embodied Agents
Language Models as Zero-Shot Planners: Extracting Actionable Knowledge for Embodied Agents [Project Page] [Paper] [Video] Wenlong Huang1, Pieter Abbee
The code used for the free quants@dev Webinar series on Reinforcement Learning in Finance
Reinforcement Learning in Finance quats@dev Webinar This repository provides the code for the free quants@dev Webinar series about Reinforcement Learn
Reading Group @mila-iqia on Computational Optimal Transport for Machine Learning Applications
Computational Optimal Transport for Machine Learning Reading Group Over the last few years, optimal transport (OT) has quickly become a central topic
Deep Learning Topics with Computer Vision & NLP
Deep learning Udacity Course Deep Learning Topics with Computer Vision & NLP for the AWS Machine Learning Engineer Nanodegree Program Tasks are mostly
Deep Learning for Morphological Profiling
Deep Learning for Morphological Profiling An end-to-end implementation of a ML System for morphological profiling using self-supervised learning to di
Predicting Keystrokes using an Audio Side-Channel Attack and Machine Learning
Predicting Keystrokes using an Audio Side-Channel Attack and Machine Learning My
FFCV: Fast Forward Computer Vision (and other ML workloads!)
Fast Forward Computer Vision: train models at a fraction of the cost with accele
This Deep Learning Model Predicts that from which disease you are suffering.
Deep-Learning-Project This Deep Learning Model Predicts that from which disease you are suffering. This Project Covers the Topics of Deep Learning Int
Titanic Traveller Survivability Prediction
The aim of the mini project is predict whether or not a passenger survived based on attributes such as their age, sex, passenger class, where they embarked and more.
Tutorial for Decision Threshold In Machine Learning.
Decision-Threshold-ML Tutorial for improve skills: 'Decision Threshold In Machine Learning' (from GeeksforGeeks) by Marcus Mariano For more informatio
Neural Machine Translation (NMT) tutorial with OpenNMT-py
Neural Machine Translation (NMT) tutorial with OpenNMT-py. Data preprocessing, model training, evaluation, and deployment.
Binary Classification Problem with Machine Learning
Binary Classification Problem with Machine Learning Solving Approach: 1) Ultimate Goal of the Assignment: This assignment is about solving a binary cl
Estimation of whether or not the persons given information will have diabetes.
Diabetes Business Problem : It is desired to develop a machine learning model that can predict whether people have diabetes when their characteristics
GNES enables large-scale index and semantic search for text-to-text, image-to-image, video-to-video and any-to-any content form
GNES is Generic Neural Elastic Search, a cloud-native semantic search system based on deep neural network.
Transformer in Vision
Transformer-in-Vision Recent Transformer-based CV and related works. Welcome to comment/contribute! Keep updated. Resource SCENIC: A JAX Library for C
A general python framework for visual object tracking and video object segmentation, based on PyTorch
PyTracking A general python framework for visual object tracking and video object segmentation, based on PyTorch. 📣 Two tracking/VOS papers accepted
Learning to Prompt for Continual Learning
Learning to Prompt for Continual Learning (L2P) Official Jax Implementation L2P is a novel continual learning technique which learns to dynamically pr
TransZero++: Cross Attribute-guided Transformer for Zero-Shot Learning
TransZero++ This repository contains the testing code for the paper "TransZero++: Cross Attribute-guided Transformer for Zero-Shot Learning" submitted
Tree Nested PyTorch Tensor Lib
DI-treetensor treetensor is a generalized tree-based tensor structure mainly developed by OpenDILab Contributors. Almost all the operation can be supp
FSL-Mate: A collection of resources for few-shot learning (FSL).
FSL-Mate is a collection of resources for few-shot learning (FSL). In particular, FSL-Mate currently contains FewShotPapers: a paper list which tracks
ECLARE: Extreme Classification with Label Graph Correlations
ECLARE ECLARE: Extreme Classification with Label Graph Correlations @InProceedings{Mittal21b, author = "Mittal, A. and Sachdeva, N. and Agrawal
GalaXC: Graph Neural Networks with Labelwise Attention for Extreme Classification
GalaXC GalaXC: Graph Neural Networks with Labelwise Attention for Extreme Classification @InProceedings{Saini21, author = {Saini, D. and Jain,
Original Implementation of Prompt Tuning from Lester, et al, 2021
Prompt Tuning This is the code to reproduce the experiments from the EMNLP 2021 paper "The Power of Scale for Parameter-Efficient Prompt Tuning" (Lest
Circuit Training: An open-source framework for generating chip floor plans with distributed deep reinforcement learning
Circuit Training: An open-source framework for generating chip floor plans with distributed deep reinforcement learning. Circuit Training is an open-s
Meta Self-learning for Multi-Source Domain Adaptation: A Benchmark
Meta Self-Learning for Multi-Source Domain Adaptation: A Benchmark Project | Arxiv | YouTube | | Abstract In recent years, deep learning-based methods
LEAP: Learning Articulated Occupancy of People
LEAP: Learning Articulated Occupancy of People Paper | Video | Project Page This is the official implementation of the CVPR 2021 submission LEAP: Lear
Code for the CVPR2021 workshop paper "Noise Conditional Flow Model for Learning the Super-Resolution Space"
NCSR: Noise Conditional Flow Model for Learning the Super-Resolution Space Official NCSR training PyTorch Code for the CVPR2021 workshop paper "Noise
Awesome AI Learning with +100 AI Cheat-Sheets, Free online Books, Top Courses, Best Videos and Lectures, Papers, Tutorials, +99 Researchers, Premium Websites, +121 Datasets, Conferences, Frameworks, Tools
All about AI with Cheat-Sheets(+100 Cheat-sheets), Free Online Books, Courses, Videos and Lectures, Papers, Tutorials, Researchers, Websites, Datasets
Consensus Learning from Heterogeneous Objectives for One-Class Collaborative Filtering
Consensus Learning from Heterogeneous Objectives for One-Class Collaborative Filtering This repository provides the source code of "Consensus Learning
Eatlocal - This package helps users solve PyBites code challenges on their local machine
eatlocal This package helps the user solve Pybites code challenges locally. Inst
Pipeline for employing a Lightweight deep learning models for LOW-power systems
PL-LOW A high-performance deep learning model lightweight pipeline that gradually lightens deep neural networks in order to utilize high-performance d
The goal of the exercises below is to evaluate the candidate knowledge and problem solving expertise regarding the main development focuses for the iFood ML Platform team: MLOps and Feature Store development.
The goal of the exercises below is to evaluate the candidate knowledge and problem solving expertise regarding the main development focuses for the iFood ML Platform team: MLOps and Feature Store development.
cl;asification problem using classification models in supervised learning
wine-quality-predition---classification cl;asification problem using classification models in supervised learning Wine Quality Prediction Analysis - C
This is a Cricket Score Predictor that predicts the first innings score of a T20 Cricket match using Machine Learning
This is a Cricket Score Predictor that predicts the first innings score of a T20 Cricket match using Machine Learning. It is a Web Application.
Machine Learning Techniques using python.
👋 Hi, I’m Fahad from TEXAS TECH. 👀 I’m interested in Optimization / Machine Learning/ Statistics 🌱 I’m currently learning Machine Learning and Stat
Learn Machine Learning Algorithms by doing projects in Python and R Programming Language
Learn Machine Learning Algorithms by doing projects in Python and R Programming Language. This repo covers all aspect of Machine Learning Algorithms.