2127 Repositories
Python delta-machine Libraries
An Empirical Investigation of Model-to-Model Distribution Shifts in Trained Convolutional Filters
CNN-Filter-DB An Empirical Investigation of Model-to-Model Distribution Shifts in Trained Convolutional Filters Paul Gavrikov, Janis Keuper Paper: htt
Explore the Expression: Facial Expression Generation using Auxiliary Classifier Generative Adversarial Network
Explore the Expression: Facial Expression Generation using Auxiliary Classifier Generative Adversarial Network This is the official implementation of
Which Style Makes Me Attractive? Interpretable Control Discovery and Counterfactual Explanation on StyleGAN
Interpretable Control Exploration and Counterfactual Explanation (ICE) on StyleGAN Which Style Makes Me Attractive? Interpretable Control Discovery an
In the AI for TSP competition we try to solve optimization problems using machine learning.
AI for TSP Competition Goal In the AI for TSP competition we try to solve optimization problems using machine learning. The competition will be hosted
PyTorch implementation of our paper How robust are discriminatively trained zero-shot learning models?
How robust are discriminatively trained zero-shot learning models? This repository contains the PyTorch implementation of our paper How robust are dis
Check out the StyleGAN repo and place it in the same directory hierarchy as the present repo
Variational Model Inversion Attacks Kuan-Chieh Wang, Yan Fu, Ke Li, Ashish Khisti, Richard Zemel, Alireza Makhzani Most commands are in run_scripts. W
CSPML (crystal structure prediction with machine learning-based element substitution)
CSPML (crystal structure prediction with machine learning-based element substitution) CSPML is a unique methodology for the crystal structure predicti
Tackling data scarcity in Speech Translation using zero-shot multilingual Machine Translation techniques
Tackling data scarcity in Speech Translation using zero-shot multilingual Machine Translation techniques This repository is derived from the NMTGMinor
Hyperparameters tuning and features selection are two common steps in every machine learning pipeline.
shap-hypetune A python package for simultaneous Hyperparameters Tuning and Features Selection for Gradient Boosting Models. Overview Hyperparameters t
A notebook that shows how to import the IITB English-Hindi Parallel Corpus from the HuggingFace datasets repository
We provide a notebook that shows how to import the IITB English-Hindi Parallel Corpus from the HuggingFace datasets repository. The notebook also shows how to segment the corpus using BPE tokenization which can be used to train an English-Hindi MT System.
A classification model capable of accurately predicting the price of secondhand cars
The purpose of this project is create a classification model capable of accurately predicting the price of secondhand cars. The data used for model building is open source and has been added to this repository. Most packages used are usually pre-installed in most developed environments and tools like collab, jupyter, etc. This can be useful for people looking to enhance the way the code their predicitve models and efficient ways to deal with tabular data!
A beginner’s guide to train and deploy machine learning pipelines in Python using PyCaret
This model involves Insurance bill prediction, which was subsequently deployed on Heroku PaaS
Audio Source Separation is the process of separating a mixture into isolated sounds from individual sources
Audio Source Separation is the process of separating a mixture into isolated sounds from individual sources (e.g. just the lead vocals).
Election Exit Poll Prediction and U.S.A Presidential Speech Analysis using Machine Learning
Machine_Learning Election Exit Poll Prediction and U.S.A Presidential Speech Analysis using Machine Learning This project is based on 2 case-studies:
This library provides an abstraction to perform Model Versioning using Weight & Biases.
Description This library provides an abstraction to perform Model Versioning using Weight & Biases. Features Version a new trained model Promote a mod
Voice Gender Recognition
In this project it was used some different Machine Learning models to identify the gender of a voice (Female or Male) based on some specific speech and voice attributes.
Annotating the Tweebank Corpus on Named Entity Recognition and Building NLP Models for Social Media Analysis
TweebankNLP This repo contains the new Tweebank-NER dataset and off-the-shelf Twitter-Stanza pipeline for state-of-the-art Tweet NLP, as described in
Neural Tangent Generalization Attacks (NTGA)
Neural Tangent Generalization Attacks (NTGA) ICML 2021 Video | Paper | Quickstart | Results | Unlearnable Datasets | Competitions | Citation Overview
On Out-of-distribution Detection with Energy-based Models
On Out-of-distribution Detection with Energy-based Models This repository contains the code for the experiments conducted in the paper On Out-of-distr
Compute execution plan: A DAG representation of work that you want to get done. Individual nodes of the DAG could be simple python or shell tasks or complex deeply nested parallel branches or embedded DAGs themselves.
Hello from magnus Magnus provides four capabilities for data teams: Compute execution plan: A DAG representation of work that you want to get done. In
Self-supervised learning (SSL) is a method of machine learning
Self-supervised learning (SSL) is a method of machine learning. It learns from unlabeled sample data. It can be regarded as an intermediate form between supervised and unsupervised learning.
This is a Deep Leaning API for classifying emotions from human face and human audios.
Emotion AI This is a Deep Leaning API for classifying emotions from human face and human audios. Starting the server To start the server first you nee
BERTopic is a topic modeling technique that leverages 🤗 transformers and c-TF-IDF to create dense clusters allowing for easily interpretable topics whilst keeping important words in the topic descriptions
BERTopic BERTopic is a topic modeling technique that leverages 🤗 transformers and c-TF-IDF to create dense clusters allowing for easily interpretable
Keepsake is a Python library that uploads files and metadata (like hyperparameters) to Amazon S3 or Google Cloud Storage
Keepsake Version control for machine learning. Keepsake is a Python library that uploads files and metadata (like hyperparameters) to Amazon S3 or Goo
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,
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
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
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
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.
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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.
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
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
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
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.
DeepFaceLive - Live Deep Fake in python, Real-time face swap for PC streaming or video calls
DeepFaceLive - Live Deep Fake in python, Real-time face swap for PC streaming or video calls
A handy tool for common machine learning models' hyper-parameter tuning.
Common machine learning models' hyperparameter tuning This repo is for a collection of hyper-parameter tuning for "common" machine learning models, in
Machine Learning Algorithms ( Desion Tree, XG Boost, Random Forest )
implementation of machine learning Algorithms such as decision tree and random forest and xgboost on darasets then compare results for each and implement ant colony and genetic algorithms on tsp map, play blackjack game and robot in grid world and evaluate reward for it
Python Computer Vision from Scratch
This repository explores the variety of techniques commonly used to analyze and interpret images. It also describes challenging real-world applications where vision is being successfully used, both for specialized applications such as medical imaging, and for fun, consumer-level tasks such as image editing and stitching, which students can apply to their own personal photos and videos.
Duke Machine Learning Winter School: Computer Vision 2022
mlwscv2002 Welcome to the Duke Machine Learning Winter School: Computer Vision 2022! The MLWS-CV includes 3 hands-on training sessions on implementing
This is the repository for The Machine Learning Workshops, published by AI DOJO
This is the repository for The Machine Learning Workshops, published by AI DOJO. It contains all the workshop's code with supporting project files necessary to work through the code.
This is the official repository of Music Playlist Title Generation: A Machine-Translation Approach.
PlyTitle_Generation This is the official repository of Music Playlist Title Generation: A Machine-Translation Approach. The paper has been accepted by
Firebase + Cloudrun + Machine learning
A simple end to end consumer lending decision engine powered by Google Cloud Platform (firebase hosting and cloudrun)
100 Days of Code Learning program to keep a habit of coding daily and learn things at your own pace with help from our remote community.
100 Days of Code Learning program to keep a habit of coding daily and learn things at your own pace with help from our remote community.
Gender Classification Machine Learning Model using Sk-learn in Python with 97%+ accuracy and deployment
Gender-classification This is a ML model to classify Male and Females using some physical characterstics Data. Python Libraries like Pandas,Numpy and
Seq2seq attn - Use the Seq2Seq method to implement machine translation and introduce Attention mechanism to improve the results
Seq2seq_attn Use the Seq2Seq method to implement machine translation and use the
Beta Shapley: a Unified and Noise-reduced Data Valuation Framework for Machine Learning
Beta Shapley: a Unified and Noise-reduced Data Valuation Framework for Machine Learning This repository provides an implementation of the paper Beta S
Used Logistic Regression, Random Forest, and XGBoost to predict the outcome of Search & Destroy games from the Call of Duty World League for the 2018 and 2019 seasons.
Call of Duty World League: Search & Destroy Outcome Predictions Growing up as an avid Call of Duty player, I was always curious about what factors led
Tripwire monitors ports and icmp to send the admin a message if somebody is scanning a machine that shouldn't be touched
Tripwire monitors ports and icmp to send the admin a message if somebody is scanning a machine that shouldn't be touched
SynapseML - an open source library to simplify the creation of scalable machine learning pipelines
Synapse Machine Learning SynapseML (previously MMLSpark) is an open source library to simplify the creation of scalable machine learning pipelines. Sy
Animal Sound Classification (Cats Vrs Dogs Audio Sentiment Classification)
this is a simple artificial neural network model using deep learning and torch-audio to classify cats and dog sounds.
PyGRANSO: A PyTorch-enabled port of GRANSO with auto-differentiation
PyGRANSO PyGRANSO: A PyTorch-enabled port of GRANSO with auto-differentiation Please check https://ncvx.org/PyGRANSO for detailed instructions (introd
Deep Learning for Time Series Forecasting.
nixtlats:Deep Learning for Time Series Forecasting [nikstla] (noun, nahuatl) Period of time. State-of-the-art time series forecasting for pytorch. Nix
In this Notebook I've build some machine-learning and deep-learning to classify corona virus tweets, in both multi class classification and binary classification.
Hello, This Notebook Contains Example of Corona Virus Tweets Multi Class Classification. - Classes is: Extremely Positive, Positive, Extremely Negativ
This is the material used in my free Persian course: Machine Learning with Python
This is the material used in my free Persian course: Machine Learning with Python
Tutorial: Introduction to Graph Machine Learning, with Jupyter notebooks
GraphMLTutorialNLDL22 Tutorial NLDL22: Introduction to Graph Machine Learning, with Jupyter notebooks This tutorial takes place during the conference
The model is designed to train a single and large neural network in order to predict correct translation by reading the given sentence.
Neural Machine Translation communication system The model is basically direct to convert one source language to another targeted language using encode