2344 Repositories
Python hierarchical-state-machine Libraries
Fast image augmentation library and an easy-to-use wrapper around other libraries
Albumentations Albumentations is a Python library for image augmentation. Image augmentation is used in deep learning and computer vision tasks to inc
A booklet on machine learning systems design with exercises
Machine Learning Systems Design Read this booklet here. This booklet covers four main steps of designing a machine learning system: Project setup Data
Can a machine learning project be implemented to estimate the salaries of baseball players whose salary information and career statistics for 1986 are shared?
END TO END MACHINE LEARNING PROJECT ON HITTERS DATASET Can a machine learning project be implemented to estimate the salaries of baseball players whos
NLP - Machine learning
Flipkart-product-reviews NLP - Machine learning About Product reviews is an essential part of an online store like Flipkartโs branding and marketing.
Cool Python features for machine learning that I used to be too afraid to use. Will be updated as I have more time / learn more.
python-is-cool A gentle guide to the Python features that I didn't know existed or was too afraid to use. This will be updated as I learn more and bec
Intrusion Detection System using ensemble learning (machine learning)
IDS-ML implementation of an intrusion detection system using ensemble machine learning methods Data set This project is carried out using the UNSW-15
A project that uses optical flow and machine learning to detect aimhacking in video clips.
waldo-anticheat A project that aims to use optical flow and machine learning to visually detect cheating or hacking in video clips from fps games. Che
Anomaly Detection Based on Hierarchical Clustering of Mobile Robot Data
We proposed a new approach to detect anomalies of mobile robot data. We investigate each data seperately with two clustering method hierarchical and k-means. There are two sub-method that we used for produce an anomaly score. Then, we merge these two score and produce merged anomaly score as a result.
This is a five-step framework for the development of intrusion detection systems (IDS) using machine learning (ML) considering model realization, and performance evaluation.
AB-TRAP: building invisibility shields to protect network devices The AB-TRAP framework is applicable to the development of Network Intrusion Detectio
PyTorch code accompanying the paper "Landmark-Guided Subgoal Generation in Hierarchical Reinforcement Learning" (NeurIPS 2021).
HIGL This is a PyTorch implementation for our paper: Landmark-Guided Subgoal Generation in Hierarchical Reinforcement Learning (NeurIPS 2021). Our cod
Dynamica causal Bayesian optimisation
Dynamic Causal Bayesian Optimization This is a Python implementation of Dynamic Causal Bayesian Optimization as presented at NeurIPS 2021. Abstract Th
Code repository for the paper: Hierarchical Kinematic Probability Distributions for 3D Human Shape and Pose Estimation from Images in the Wild (ICCV 2021)
Hierarchical Kinematic Probability Distributions for 3D Human Shape and Pose Estimation from Images in the Wild Akash Sengupta, Ignas Budvytis, Robert
This repository contains the implementation of the paper: "Towards Frequency-Based Explanation for Robust CNN"
RobustFreqCNN About This repository contains the implementation of the paper "Towards Frequency-Based Explanation for Robust CNN" arxiv. It primarly d
In this project I played with mlflow, streamlit and fastapi to create a training and prediction app on digits
Fastapi + MLflow + streamlit Setup env. I hope I covered all. pip install -r requirements.txt Start app Go in the root dir and run these Streamlit str
(Py)TOD: Tensor-based Outlier Detection, A General GPU-Accelerated Framework
(Py)TOD: Tensor-based Outlier Detection, A General GPU-Accelerated Framework Background: Outlier detection (OD) is a key data mining task for identify
A PyTorch Lightning Callback for pushing models to the Hugging Face Hub ๐คโก๏ธ
hf-hub-lightning A callback for pushing lightning models to the Hugging Face Hub. Note: I made this package for myself, mostly...if folks seem to be i
Machine Translation Implement By Bi-GRU And Transformer
Seq2Seq Translation Implement By Bidirectional GRU And Transformer In Pytorch Before You Run The Code You should download the data through the link be
A lightweight python AUTOmatic-arRAY library.
A lightweight python AUTOmatic-arRAY library. Write numeric code that works for: numpy cupy dask autograd jax mars tensorflow pytorch ... and indeed a
Simple PyTorch hierarchical models.
A python package adding basic hierarchal networks in pytorch for classification tasks. It implements a simple hierarchal network structure based on feed-backward outputs.
A Nim frontend for pytorch, aiming to be mostly auto-generated and internally using ATen.
Master Release Pytorch - Py + Nim A Nim frontend for pytorch, aiming to be mostly auto-generated and internally using ATen. Because Nim compiles to C+
Anuvada: Interpretable Models for NLP using PyTorch
Anuvada: Interpretable Models for NLP using PyTorch So, you want to know why your classifier arrived at a particular decision or why your flashy new d
A method for cleaning and classifying text using transformers.
NLP Translation and Classification The repository contains a method for classifying and cleaning text using NLP transformers. Overview The input data
Simple Machine Learning Tool Kit
Getting started smltk (Simple Machine Learning Tool Kit) package is implemented for helping your work during data preparation testing your model The g
NeurIPS 2021, "Fine Samples for Learning with Noisy Labels"
[Official] FINE Samples for Learning with Noisy Labels This repository is the official implementation of "FINE Samples for Learning with Noisy Labels"
Connection package to a raspberry or any other machine using ssh, it simplifies the deployment scripts and monitoring.
Connection package to a raspberry or any other machine using ssh, it simplifies the deployment scripts and monitoring.
DirectML is a high-performance, hardware-accelerated DirectX 12 library for machine learning.
DirectML is a high-performance, hardware-accelerated DirectX 12 library for machine learning. DirectML provides GPU acceleration for common machine learning tasks across a broad range of supported hardware and drivers, including all DirectX 12-capable GPUs from vendors such as AMD, Intel, NVIDIA, and Qualcomm.
Hierarchical Few-Shot Generative Models
Hierarchical Few-Shot Generative Models Giorgio Giannone, Ole Winther This repo contains code and experiments for the paper Hierarchical Few-Shot Gene
Hierarchical probabilistic 3D U-Net, with attention mechanisms (โ๐๐ต๐ต๐ฆ๐ฏ๐ต๐ช๐ฐ๐ฏ ๐-๐๐ฆ๐ต, ๐๐๐๐ฆ๐ด๐๐ฆ๐ต) and a nested decoder structure with deep supervision (โ๐๐๐ฆ๐ต++).
Hierarchical probabilistic 3D U-Net, with attention mechanisms (โ๐๐ต๐ต๐ฆ๐ฏ๐ต๐ช๐ฐ๐ฏ ๐-๐๐ฆ๐ต, ๐๐๐๐ฆ๐ด๐๐ฆ๐ต) and a nested decoder structure with deep supervision (โ๐๐๐ฆ๐ต++). Built in TensorFlow 2.5. Configured for voxel-level clinically significant prostate cancer detection in multi-channel 3D bpMRI scans.
Assessing the Influence of Models on the Performance of Reinforcement Learning Algorithms applied on Continuous Control Tasks
Assessing the Influence of Models on the Performance of Reinforcement Learning Algorithms applied on Continuous Control Tasks This is the master thesi
๐ค Transformers: State-of-the-art Natural Language Processing for Pytorch, TensorFlow, and JAX.
English | ็ฎไฝไธญๆ | ็น้ซไธญๆ | ํ๊ตญ์ด State-of-the-art Natural Language Processing for Jax, PyTorch and TensorFlow ๐ค Transformers provides thousands of pretrai
Jiminy Cricket Environment (NeurIPS 2021)
Jiminy Cricket This is the repository for "What Would Jiminy Cricket Do? Towards Agents That Behave Morally" by Dan Hendrycks*, Mantas Mazeika*, Andy
A simple voice detection system which can be applied practically for designing a device with capability to detect a babyโs cry and automatically turning on music
Auto-Baby-Cry-Detection-with-Music-Player A simple voice detection system which can be applied practically for designing a device with capability to d
Implementation of ConvMixer-Patches Are All You Need? in TensorFlow and Keras
Patches Are All You Need? - ConvMixer ConvMixer, an extremely simple model that is similar in spirit to the ViT and the even-more-basic MLP-Mixer in t
๐ต A repository for manually annotating files to create labeled acoustic datasets for machine learning.
๐ต A repository for manually annotating files to create labeled acoustic datasets for machine learning.
A little Python application to auto tag your photos with the power of machine learning.
Tag Machine A little Python application to auto tag your photos with the power of machine learning. Report a bug or request a feature Table of Content
Official implementation of "Learning Proposals for Practical Energy-Based Regression", 2021.
ebms_proposals Official implementation (PyTorch) of the paper: Learning Proposals for Practical Energy-Based Regression, 2021 [arXiv] [project]. Fredr
PyTorch framework for Deep Learning research and development.
Accelerated DL & RL PyTorch framework for Deep Learning research and development. It was developed with a focus on reproducibility, fast experimentati
Convolutional Recurrent Neural Network (CRNN) for image-based sequence recognition.
Convolutional Recurrent Neural Network This software implements the Convolutional Recurrent Neural Network (CRNN), a combination of CNN, RNN and CTC l
Convolutional Neural Network for 3D meshes in PyTorch
MeshCNN in PyTorch SIGGRAPH 2019 [Paper] [Project Page] MeshCNN is a general-purpose deep neural network for 3D triangular meshes, which can be used f
Adaptive, interpretable wavelets across domains (NeurIPS 2021)
Adaptive wavelets Wavelets which adapt given data (and optionally a pre-trained model). This yields models which are faster, more compressible, and mo
PyTorch Implementation of Unsupervised Depth Completion with Calibrated Backprojection Layers (ORAL, ICCV 2021)
Unsupervised Depth Completion with Calibrated Backprojection Layers PyTorch implementation of Unsupervised Depth Completion with Calibrated Backprojec
This is a Machine Learning Based Hand Detector Project, It Uses Machine Learning Models and Modules Like Mediapipe, Developed By Google!
Machine Learning Hand Detector This is a Machine Learning Based Hand Detector Project, It Uses Machine Learning Models and Modules Like Mediapipe, Dev
database for artificial intelligence/machine learning data
AIDB v0.0.1 database for artificial intelligence/machine learning data Overview aidb is a database designed for large dataset for machine learning pro
PyTorch Implementation of Unsupervised Depth Completion with Calibrated Backprojection Layers (ORAL, ICCV 2021)
PyTorch Implementation of Unsupervised Depth Completion with Calibrated Backprojection Layers (ORAL, ICCV 2021)
Open-source Laplacian Eigenmaps for dimensionality reduction of large data in python.
Fast Laplacian Eigenmaps in python Open-source Laplacian Eigenmaps for dimensionality reduction of large data in python. Comes with an wrapper for NMS
This is the code of NeurIPS'21 paper "Towards Enabling Meta-Learning from Target Models".
ST This is the code of NeurIPS 2021 paper "Towards Enabling Meta-Learning from Target Models". If you use any content of this repo for your work, plea
A project that uses optical flow and machine learning to detect aimhacking in video clips.
waldo-anticheat A project that aims to use optical flow and machine learning to visually detect cheating or hacking in video clips from fps games. Che
Code for "Hierarchical Skills for Efficient Exploration" HSD-3 Algorithm and Baselines
Hierarchical Skills for Efficient Exploration This is the source code release for the paper Hierarchical Skills for Efficient Exploration. It contains
Stochastic Gradient Trees implementation in Python
Stochastic Gradient Trees - Python Stochastic Gradient Trees1 by Henry Gouk, Bernhard Pfahringer, and Eibe Frank implementation in Python. Based on th
Code for reproducing our paper: LMSOC: An Approach for Socially Sensitive Pretraining
LMSOC: An Approach for Socially Sensitive Pretraining Code for reproducing the paper LMSOC: An Approach for Socially Sensitive Pretraining to appear a
Extremely simple and fast extreme multi-class and multi-label classifiers.
napkinXC napkinXC is an extremely simple and fast library for extreme multi-class and multi-label classification, that focus of implementing various m
PyImpetus is a Markov Blanket based feature subset selection algorithm that considers features both separately and together as a group in order to provide not just the best set of features but also the best combination of features
PyImpetus PyImpetus is a Markov Blanket based feature selection algorithm that selects a subset of features by considering their performance both indi
BMVC 2021: This is the github repository for "Few Shot Temporal Action Localization using Query Adaptive Transformers" accepted in British Machine Vision Conference (BMVC) 2021, Virtual
FS-QAT: Few Shot Temporal Action Localization using Query Adaptive Transformer Accepted as Poster in BMVC 2021 This is an official implementation in P
A PyTorch-centric hybrid classical-quantum machine learning framework
torchquantum A PyTorch-centric hybrid classical-quantum dynamic neural networks framework. News Add a simple example script using quantum gates to do
An Industrial Grade Federated Learning Framework
DOC | Quick Start | ไธญๆ FATE (Federated AI Technology Enabler) is an open-source project initiated by Webank's AI Department to provide a secure comput
OpenABC-D: A Large-Scale Dataset For Machine Learning Guided Integrated Circuit Synthesis
OpenABC-D: A Large-Scale Dataset For Machine Learning Guided Integrated Circuit Synthesis Overview OpenABC-D is a large-scale labeled dataset generate
This is a tool to help people to make a bot for labelling images for machine learning projects.
labeller_images_python_telegramBOT This is a bot to help collect data for any machine learning project. It was developed using the python-telegram-bot
Implicit hierarchical a posteriori error estimates in FEniCSx
FEniCSx Error Estimation (FEniCSx-EE) Description FEniCSx-EE is an open source library showing how various error estimation strategies can be implemen
[CVPR 2021] Generative Hierarchical Features from Synthesizing Images
[CVPR 2021] Generative Hierarchical Features from Synthesizing Images
Blue Brain text mining toolbox for semantic search and structured information extraction
Blue Brain Search Source Code DOI Data & Models DOI Documentation Latest Release Python Versions License Build Status Static Typing Code Style Securit
ml4ir: Machine Learning for Information Retrieval
ml4ir: Machine Learning for Information Retrieval | changelog Quickstart โ ml4ir Read the Docs | ml4ir pypi | python ReadMe ml4ir is an open source li
A library for Deep Learning Implementations and utils
deeply A Deep Learning library Table of Contents Features Quick Start Usage License Features Python 2.7+ and Python 3.4+ compatible. Quick Start $ pip
Website which uses Deep Learning to generate horror stories.
Creepypasta - Text Generator Website which uses Deep Learning to generate horror stories. View Demo ยท View Website Repo ยท Report Bug ยท Request Feature
LWCC: A LightWeight Crowd Counting library for Python that includes several pretrained state-of-the-art models.
LWCC: A LightWeight Crowd Counting library for Python LWCC is a lightweight crowd counting framework for Python. It wraps four state-of-the-art models
Deepparse is a state-of-the-art library for parsing multinational street addresses using deep learning
Here is deepparse. Deepparse is a state-of-the-art library for parsing multinational street addresses using deep learning. Use deepparse to Use the pr
The end-to-end platform for building voice products at scale
Picovoice Made in Vancouver, Canada by Picovoice Picovoice is the end-to-end platform for building voice products on your terms. Unlike Alexa and Goog
A multi-functional library for full-stack Deep Learning. Simplifies Model Building, API development, and Model Deployment.
chitra What is chitra? chitra (เคเคฟเคคเฅเคฐ) is a multi-functional library for full-stack Deep Learning. It simplifies Model Building, API development, and M
Differentiable scientific computing library
xitorch: differentiable scientific computing library xitorch is a PyTorch-based library of differentiable functions and functionals that can be widely
ML From Scratch
ML from Scratch MACHINE LEARNING TOPICS COVERED - FROM SCRATCH Linear Regression Logistic Regression K Means Clustering K Nearest Neighbours Decision
A MNIST-like fashion product database. Benchmark
Fashion-MNIST Table of Contents Why we made Fashion-MNIST Get the Data Usage Benchmark Visualization Contributing Contact Citing Fashion-MNIST License
A plug-and-play library for neural networks written in Python
A plug-and-play library for neural networks written in Python!
Deep Learning to Create StepMania SM FIles
StepCOVNet Running Audio to SM File Generator Currently only produces .txt files. Use SMDataTools to convert .txt to .sm python stepmania_note_generat
General purpose GPU compute framework for cross vendor graphics cards (AMD, Qualcomm, NVIDIA & friends)
General purpose GPU compute framework for cross vendor graphics cards (AMD, Qualcomm, NVIDIA & friends). Blazing fast, mobile-enabled, asynchronous and optimized for advanced GPU data processing usecases. Backed by the Linux Foundation.
Machine Leaning applied to denoise images to improve OCR Accuracy
Machine Learning to Denoise Images for Better OCR Accuracy This project is an adaptation of this tutorial and used only for learning purposes: https:/
Train a state-of-the-art yolov3 object detector from scratch!
TrainYourOwnYOLO: Building a Custom Object Detector from Scratch This repo let's you train a custom image detector using the state-of-the-art YOLOv3 c
VerSign: Easy Signature Verification in Python
VerSign: Easy Signature Verification in Python versign is a small Python package which can be used to perform verification of offline signatures. It a
Deep learning library for solving differential equations and more
DeepXDE Voting on whether we should have a Slack channel for discussion. DeepXDE is a library for scientific machine learning. Use DeepXDE if you need
A Real-Time-Strategy game for Deep Learning research
Description DeepRTS is a high-performance Real-TIme strategy game for Reinforcement Learning research. It is written in C++ for performance, but provi
Using machine learning to predict and analyze high and low reader engagement for New York Times articles posted to Facebook.
How The New York Times can increase Engagement on Facebook Using machine learning to understand characteristics of news content that garners "high" Fa
Code repository of the paper Neural circuit policies enabling auditable autonomy published in Nature Machine Intelligence
Code repository of the paper Neural circuit policies enabling auditable autonomy published in Nature Machine Intelligence
Retentioneering: product analytics, data-driven customer journey map optimization, marketing analytics, web analytics, transaction analytics, graph visualization, and behavioral segmentation with customer segments in Python.
What is Retentioneering? Retentioneering is a Python framework and library to assist product analysts and marketing analysts as it makes it easier to
๐ฅ๐ฅHigh-Performance Face Recognition Library on PaddlePaddle & PyTorch๐ฅ๐ฅ
face.evoLVe: High-Performance Face Recognition Library based on PaddlePaddle & PyTorch Evolve to be more comprehensive, effective and efficient for fa
Nixtla is an open-source time series forecasting library.
Nixtla Nixtla is an open-source time series forecasting library. We are helping data scientists and developers to have access to open source state-of-
RealTime Emotion Recognizer for Machine Learning Study Jam's demo
Emotion recognizer Table of contents Clone project Dataset Install dependencies Main program Demo 1. Clone project git clone https://github.com/GDSC20
Deep Learning Interviews book: Hundreds of fully solved job interview questions from a wide range of key topics in AI.
This book was written for you: an aspiring data scientist with a quantitative background, facing down the gauntlet of the interview process in an increasingly competitive field. For most of you, the interview process is the most significant hurdle between you and a dream job.
DaCeML - Machine learning powered by data-centric parallel programming.
Data-centric machine learning powered by DaCe
Apple-voice-recognition - Machine Learning
Apple-voice-recognition Machine Learning How does Siri work? Siri is based on large-scale Machine Learning systems that employ many aspects of data sc
This repository demonstrates the usage of hover to understand and supervise a machine learning task.
Hover Example Apps (works out-of-the-box on Binder) This repository demonstrates the usage of hover to understand and supervise a machine learning tas
Vector AI โ A platform for building vector based applications. Encode, query and analyse data using vectors.
Vector AI is a framework designed to make the process of building production grade vector based applications as quickly and easily as possible. Create
A Deep Learning based project for creating line art portraits.
ArtLine The main aim of the project is to create amazing line art portraits. Sounds Intresting,let's get to the pictures!! Model-(Smooth) Model-(Quali
๐ท This repository is focused on having various feature implementation of OpenCV in Python.
๐ท This repository is focused on having various feature implementation of OpenCV in Python. The aim is to have a minimal implementation of all OpenCV features together, under one roof.
10x faster matrix and vector operations
Bolt is an algorithm for compressing vectors of real-valued data and running mathematical operations directly on the compressed representations. If yo
Synthetic structured data generators
Join us on What is Synthetic Data? Synthetic data is artificially generated data that is not collected from real world events. It replicates the stati
This is a collection of simple PyTorch implementations of neural networks and related algorithms. These implementations are documented with explanations,
labml.ai Deep Learning Paper Implementations This is a collection of simple PyTorch implementations of neural networks and related algorithms. These i
DeepMind's software stack for physics-based simulation and Reinforcement Learning environments, using MuJoCo.
dm_control: DeepMind Infrastructure for Physics-Based Simulation. DeepMind's software stack for physics-based simulation and Reinforcement Learning en
Code repository of the paper Neural circuit policies enabling auditable autonomy published in Nature Machine Intelligence
Neural Circuit Policies Enabling Auditable Autonomy Online access via SharedIt Neural Circuit Policies (NCPs) are designed sparse recurrent neural net
High-quality implementations of standard and SOTA methods on a variety of tasks.
Uncertainty Baselines The goal of Uncertainty Baselines is to provide a template for researchers to build on. The baselines can be a starting point fo
Official PyTorch Implementation of HELP: Hardware-adaptive Efficient Latency Prediction for NAS via Meta-Learning (NeurIPS 2021 Spotlight)
[NeurIPS 2021 Spotlight] HELP: Hardware-adaptive Efficient Latency Prediction for NAS via Meta-Learning [Paper] This is Official PyTorch implementatio
Identify the emotion of multiple speakers in an Audio Segment
MevonAI - Speech Emotion Recognition Identify the emotion of multiple speakers in a Audio Segment Report Bug ยท Request Feature Try the Demo Here Table
This repository contains the code for the paper in EMNLP 2021: "HRKD: Hierarchical Relational Knowledge Distillation for Cross-domain Language Model Compression".
HRKD: Hierarchical Relational Knowledge Distillation for Cross-domain Language Model Compression This repository contains the code for the paper in EM