3121 Repositories
Python NLU-training-data Libraries
Explaining Deep Neural Networks - A comparison of different CAM methods based on an insect data set
Explaining Deep Neural Networks - A comparison of different CAM methods based on an insect data set This is the repository for the Deep Learning proje
CMSC320 - Introduction to Data Science - Fall 2021
CMSC320 - Introduction to Data Science - Fall 2021 Instructors: Elias Jonatan Gonzalez and José Manuel Calderón Trilla Lectures: MW 3:30-4:45 & 5:00-6
clustering moroccan stocks time series data using k-means with dtw (dynamic time warping)
Moroccan Stocks Clustering Context Hey! we don't always have to forecast time series am I right ? We use k-means to cluster about 70 moroccan stock pr
This repository contains project created during the Data Challenge module at London School of Hygiene & Tropical Medicine
LSHTM_RCS This repository contains project created during the Data Challenge module at London School of Hygiene & Tropical Medicine (LSHTM) in collabo
Data Engineering ZoomCamp
Data Engineering ZoomCamp I'm partaking in a Data Engineering Bootcamp / Zoomcamp and will be tracking my progress here. I can't promise these notes w
Processed, version controlled history of Minecraft's generated data and assets
mcmeta Processed, version controlled history of Minecraft's generated data and assets Repository structure Each of the following branches has a commit
A web app builds using streamlit API with python backend to analyze and pick insides from multiple data formats.
Data-Analysis-Web-App Data Analysis Web App can analysis data in multiple formates(csv, txt, xls, xlsx, ods, odt) and gives shows you the analysis in
Training DiffWave using variational method from Variational Diffusion Models.
Variational DiffWave Training DiffWave using variational method from Variational Diffusion Models. Quick Start python train_distributed.py discrete_10
BaseCls BaseCls 是一个基于 MegEngine 的预训练模型库,帮助大家挑选或训练出更适合自己科研或者业务的模型结构
BaseCls BaseCls 是一个基于 MegEngine 的预训练模型库,帮助大家挑选或训练出更适合自己科研或者业务的模型结构。 文档地址:https://basecls.readthedocs.io 安装 安装环境 BaseCls 需要 Python = 3.6。 BaseCls 依赖 M
TIANCHI Purchase Redemption Forecast Challenge
TIANCHI Purchase Redemption Forecast Challenge
WikiPron - a command-line tool and Python API for mining multilingual pronunciation data from Wiktionary
WikiPron WikiPron is a command-line tool and Python API for mining multilingual pronunciation data from Wiktionary, as well as a database of pronuncia
Import some key/value data to Prometheus custom-built Node Exporter in Python
About the app In one particilar project, i had to import some key/value data to Prometheus. So i have decided to create my custom-built Node Exporter
Machine Learning e Data Science com Python
Machine Learning e Data Science com Python Arquivos do curso de Data Science e Machine Learning com Python na Udemy, cliqe aqui para acessá-lo. O prin
Clean and reusable data-sciency notebooks.
KPACUBO KPACUBO is a set Jupyter notebooks focused on the best practices in both software development and data science, namely, code reuse, explicit d
This repository contains the raw data and a python notebook to ingest historical A&E attendance data and then use a simple Prophet model to predict the number of A&E attendances in England if the COVID-19 pandemic had not happened
ae_attendances_modelling This repository contains the raw data and a python notebook to ingest historical A&E attendance data and then use a simple Pr
FAIR Enough Metrics is an API for various FAIR Metrics Tests, written in python
☑️ FAIR Enough metrics for research FAIR Enough Metrics is an API for various FAIR Metrics Tests, written in python, conforming to the specifications
This repository contains the implementation of the HealthGen model, a generative model to synthesize realistic EHR time series data with missingness
HealthGen: Conditional EHR Time Series Generation This repository contains the implementation of the HealthGen model, a generative model to synthesize
JASS: Japanese-specific Sequence to Sequence Pre-training for Neural Machine Translation
JASS: Japanese-specific Sequence to Sequence Pre-training for Neural Machine Translation This the repository for this paper. Find extensions of this w
WPPNets: Unsupervised CNN Training with Wasserstein Patch Priors for Image Superresolution
WPPNets: Unsupervised CNN Training with Wasserstein Patch Priors for Image Superresolution This code belongs to the paper [1] available at https://arx
A PyTorch implementation for our paper "Dual Contrastive Learning: Text Classification via Label-Aware Data Augmentation".
Dual-Contrastive-Learning A PyTorch implementation for our paper "Dual Contrastive Learning: Text Classification via Label-Aware Data Augmentation". Y
For encoding a text longer than 512 tokens, for example 800. Set max_pos to 800 during both preprocessing and training.
LongScientificFormer For encoding a text longer than 512 tokens, for example 800. Set max_pos to 800 during both preprocessing and training. Some code
PyTorch implementation for the paper Visual Representation Learning with Self-Supervised Attention for Low-Label High-Data Regime
Visual Representation Learning with Self-Supervised Attention for Low-Label High-Data Regime Created by Prarthana Bhattacharyya. Disclaimer: This is n
Framework for training options with different attention mechanism and using them to solve downstream tasks.
Using Attention in HRL Framework for training options with different attention mechanism and using them to solve downstream tasks. Requirements GPU re
coldcuts is an R package to automatically generate and plot segmentation drawings in R
coldcuts coldcuts is an R package that allows you to draw and plot automatically segmentations from 3D voxel arrays. The name is inspired by one of It
Identifying a Training-Set Attack’s Target Using Renormalized Influence Estimation
Identifying a Training-Set Attack’s Target Using Renormalized Influence Estimation By: Zayd Hammoudeh and Daniel Lowd Paper: Arxiv Preprint Coming soo
Post-training Quantization for Neural Networks with Provable Guarantees
Post-training Quantization for Neural Networks with Provable Guarantees Authors: Jinjie Zhang ([email protected]), Yixuan Zhou ([email protected]) and Ray
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
Semantic code search implementation using Tensorflow framework and the source code data from the CodeSearchNet project
Semantic Code Search Semantic code search implementation using Tensorflow framework and the source code data from the CodeSearchNet project. The model
Code for the paper titled "Prabhupadavani: A Code-mixed Speech Translation Data for 25 languages"
Prabhupadavani: A Code-mixed Speech Translation Data for 25 languages Code for the paper titled "Prabhupadavani: A Code-mixed Speech Translation Data
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!
Analyzing Earth Observation (EO) data is complex and solutions often require custom tailored algorithms.
eo-grow Earth observation framework for scaled-up processing in Python. Analyzing Earth Observation (EO) data is complex and solutions often require c
Statistical & Probabilistic Analysis of Store Sales, University Survey, & Manufacturing data
Statistical_Modelling Statistical & Probabilistic Analysis of Store Sales, University Survey, & Manufacturing data Statistical Methods for Decision Ma
Melanoma Skin Cancer Detection using Convolutional Neural Networks and Transfer Learning🕵🏻♂️
This is a Kaggle competition in which we have to identify if the given lesion image is malignant or not for Melanoma which is a type of skin cancer.
Final Project for Practical Python Programming and Algorithms for Data Analysis
Final Project for Practical Python Programming and Algorithms for Data Analysis (PHW2781L, Summer 2020) Redlining, Race-Exclusive Deed Restriction Lan
Fetch fund data from avanza.se using Python and some web scraping with bs4
Py(A)vanza Fetch fund data from avanza.se using Python and some web scraping with bs4. The default way is to display the data in the terminal, apply -
Storing, versioning, and downloading files from S3 made as easy as using open() in Python. Caching included.
open(LARGE) Storing, versioning, and downloading files from S3 made as easy as using open() in Python. Caching included. Motivation Oftentimes, especi
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
Python-geoarrow - Storing geometry data in Apache Arrow format
geoarrow Storing geometry data in Apache Arrow format Installation $ pip install
Scikit-event-correlation - Event Correlation and Forecasting over High Dimensional Streaming Sensor Data algorithms
scikit-event-correlation Event Correlation and Changing Detection Algorithm Theo
Graviti-python-sdk - Graviti Data Platform Python SDK
Graviti Python SDK Graviti Python SDK is a python library to access Graviti Data
DomainMonitor is a web project that has a RESTful API to get a domain's subdomains and whois data.
DomainMonitor is a web project that has a RESTful API to get a domain's subdomains and whois data.
OptiPLANT is a cloud-based based system that empowers professional and non-professional data scientists to build high-quality predictive models
OptiPLANT OptiPLANT is a cloud-based based system that empowers professional and non-professional data scientists to build high-quality predictive mod
Dynamic vae - Dynamic VAE algorithm is used for anomaly detection of battery data
Dynamic VAE frame Automatic feature extraction can be achieved by probability di
SAS: Self-Augmentation Strategy for Language Model Pre-training
SAS: Self-Augmentation Strategy for Language Model Pre-training This repository
This repo provides the source code & data of our paper "GreaseLM: Graph REASoning Enhanced Language Models"
GreaseLM: Graph REASoning Enhanced Language Models This repo provides the source code & data of our paper "GreaseLM: Graph REASoning Enhanced Language
Revisiting Weakly Supervised Pre-Training of Visual Perception Models
SWAG: Supervised Weakly from hashtAGs This repository contains SWAG models from the paper Revisiting Weakly Supervised Pre-Training of Visual Percepti
Cycle Self-Training for Domain Adaptation (NeurIPS 2021)
CST Code release for "Cycle Self-Training for Domain Adaptation" (NeurIPS 2021) Prerequisites torch=1.7.0 torchvision qpsolvers numpy prettytable tqd
Clustering is a popular approach to detect patterns in unlabeled data
Visual Clustering Clustering is a popular approach to detect patterns in unlabeled data. Existing clustering methods typically treat samples in a data
SpyQL - SQL with Python in the middle
SpyQL SQL with Python in the middle Concept SpyQL is a query language that combines: the simplicity and structure of SQL with the power and readabilit
Data-sets from the survey and analysis
bachelor-thesis "Umfragewerte.xlsx" contains the orginal survey results. "umfrage_alle.csv" contains the survey results but one participant is cancele
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
Es-schema - Common Data Schemas for Elasticsearch
Common Data Schemas for Elasticsearch The Common Data Schema for Elasticsearch i
Data analysis and visualisation projects from a range of individual projects and applications
Python-Data-Analysis-and-Visualisation-Projects Data analysis and visualisation projects from a range of individual projects and applications. Python
Predicting Auction Sale Price using the kaggle bulldozer auction sales data: Modeling with Ensembles vs Neural Network
Predicting Auction Sale Price using the kaggle bulldozer auction sales data: Modeling with Ensembles vs Neural Network The performances of tree ensemb
A program made in PYTHON🐍 that automatically performs data insertions into a POSTGRES database 🐘 , using as base a .CSV file 📁 , useful in mass data insertions
A program made in PYTHON🐍 that automatically performs data insertions into a POSTGRES database 🐘 , using as base a .CSV file 📁 , useful in mass data insertions.
Labelbox is the fastest way to annotate data to build and ship artificial intelligence applications
Labelbox Labelbox is the fastest way to annotate data to build and ship artificial intelligence applications. Use this github repository to help you s
CLIP (Contrastive Language-Image Pre-Training) is a neural network trained on a variety of (image, text) pairs
CLIP [Blog] [Paper] [Model Card] [Colab] CLIP (Contrastive Language-Image Pre-Training) is a neural network trained on a variety of (image, text) pair
FairLens is an open source Python library for automatically discovering bias and measuring fairness in data
FairLens FairLens is an open source Python library for automatically discovering bias and measuring fairness in data. The package can be used to quick
The repository includes the code for training cell counting applications. (Keras + Tensorflow)
cell_counting_v2 The repository includes the code for training cell counting applications. (Keras + Tensorflow) Dataset can be downloaded here : http:
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,
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.
Segmentation Training Pipeline
Segmentation Training Pipeline This package is a part of Musket ML framework. Reasons to use Segmentation Pipeline Segmentation Pipeline was developed
PyTorchMemTracer - Depict GPU memory footprint during DNN training of PyTorch
A Memory Tracer For PyTorch OOM is a nightmare for PyTorch users. However, most
Equipped customers with insights about their EVs Hourly energy consumption and helped predict future charging behavior using LSTM model
Equipped customers with insights about their EVs Hourly energy consumption and helped predict future charging behavior using LSTM model. Designed sample dashboard with insights and recommendation for customers.
First steps with Python in Life Sciences
First steps with Python in Life Sciences This course material is part of the "First Steps with Python in Life Science" three-day course of SIB-trainin
A Celery application to collect data, download media and extract information from social media APIs
Project IBEX A Celery application to collect data, download media and extract information from social media APIs. Requirements You must have a Redis D
Data processing with Pandas.
Processing-data-with-python This is a simple example showing how to use Pandas to create a dataframe and the processing data with python. The jupyter
Nobel Data Analysis
Nobel_Data_Analysis This project is for analyzing a set of data about people who have won the Nobel Prize in different fields and different countries
Investigating EV charging data
Investigating EV charging data Introduction: Got an opportunity to work with a home monitoring technology company over the last 6 months whose goal wa
Analyze the Gravitational wave data stored at LIGO/VIRGO observatories
Gravitational-Wave-Analysis This project showcases how to analyze the Gravitational wave data stored at LIGO/VIRGO observatories, using Python program
This python script allows you to manipulate the audience data from Sl.ido surveys
Slido-Automated-VoteBot This python script allows you to manipulate the audience data from Sl.ido surveys Since Slido blocks interference from automat
Cormen-Lib - An academic tool for data structures and algorithms courses
The Cormen-lib module is an insular data structures and algorithms library based on the Thomas H. Cormen's Introduction to Algorithms Third Edition. This library was made specifically for administering and grading assignments related to data structure and algorithms in computer science.
Collapse by Conditioning: Training Class-conditional GANs with Limited Data
Collapse by Conditioning: Training Class-conditional GANs with Limited Data Moha
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
GoogleFormSpammer - A simple CLI script to spam Google Forms used by Crypto Wallet scammers to collect stolen data
GoogleFormSpammer - A simple CLI script to spam Google Forms used by Crypto Wallet scammers to collect stolen data
Implement the Perspective open source code in preparation for data visualization
Task Overview | Installation Instructions | Link to Module 2 Introduction Experience Technology at JP Morgan Chase Try out what real work is like in t
PostQF is a user-friendly Postfix queue data filter which operates on data produced by postqueue -j.
PostQF Copyright © 2022 Ralph Seichter PostQF is a user-friendly Postfix queue data filter which operates on data produced by postqueue -j. See the ma
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.
Learn Basic to advanced level Data visualisation techniques from this Repository
Data visualisation Hey, You can learn Basic to advanced level Data visualisation techniques from this Repository. Data visualization is the graphic re
Create charts with Python in a very similar way to creating charts using Chart.js
Create charts with Python in a very similar way to creating charts using Chart.js. The charts created are fully configurable, interactive and modular and are displayed directly in the output of the the cells of your jupyter notebook environment.
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
Equibles Stocks API for Python
Equibles Stocks API for Python Requirements. Python 2.7 and 3.4+ Installation & Usage pip install If the python package is hosted on Github, you can i
A server and client for passing data between computercraft computers/turtles across dimensions or even servers.
ccserver A server and client for passing data between computercraft computers/turtles across dimensions or even servers. pastebin get zUnE5N0v client
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
INFO-H515 - Big Data Scalable Analytics
INFO-H515 - Big Data Scalable Analytics Jacopo De Stefani, Giovanni Buroni, Théo Verhelst and Gianluca Bontempi - Machine Learning Group Exercise clas
This module is used to create Convolutional AutoEncoders for Variational Data Assimilation
VarDACAE This module is used to create Convolutional AutoEncoders for Variational Data Assimilation. A user can define, create and train an AE for Dat
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
Perform sentiment analysis on textual data that people generally post on websites like social networks and movie review sites.
Sentiment Analyzer The goal of this project is to perform sentiment analysis on textual data that people generally post on websites like social networ
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.
Python for Data Analysis, 2nd Edition
Python for Data Analysis, 2nd Edition Materials and IPython notebooks for "Python for Data Analysis" by Wes McKinney, published by O'Reilly Media Buy
INF42 - Topological Data Analysis
TDA INF421(Conception et analyse d'algorithmes) Projet : Topological Data Analysis SphereMin Etant donné un nuage des points, ce programme contient de
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
sequitur is a library that lets you create and train an autoencoder for sequential data in just two lines of code
sequitur sequitur is a library that lets you create and train an autoencoder for sequential data in just two lines of code. It implements three differ
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
This is an analysis and prediction project for house prices in King County, USA based on certain features of the house
This is a project for analysis and estimation of House Prices in King County USA The .csv file contains the data of the house and the .ipynb file con
Repo for investigation of timeouts that happens with prolonged training on clients
Flower-timeout Repo for investigation of timeouts that happens with prolonged training on clients. This repository is meant purely for demonstration o