Python Huggingface-sagemaker-workshop-series Resources

SageMaker Projects: Multiple Choice Deployment A SageMaker Projects template to deploy a model from Model Registry, choosing your preferred method of

feature-set-comp Compares various time-series feature sets on computational performance, within-set structure, and between-set relationships. Reposito

Transformer Embedder A Word Level Transformer layer based on PyTorch and 🤗 Transformers. How to use Install the library from PyPI: pip install transf

petnica-api-workshop Just RESTing Setup Using pipenv You can setup this project with pipenv if you want isolated libraries. After you've installed pip

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-

PyEmits, a python package for easy manipulation in time-series data. Time-series data is very common in real life. Engineering FSI industry (Financial

Material de demonstração dos serviços: Watson Natural Language Understanding e Knowledge Studio Visão Geral: https://www.ibm.com/br-pt/cloud/watson-na

Tracking Code for the winner of track1 in MMP-Trakcing challenge This repository contains our tracking code for the Multi-camera Multiple People Track

Codebase for Time-series Generative Adversarial Networks (TimeGAN)

TimeGAN-pytorch Pytorch implementation of the paper Time-series Generative Adversarial Networks presented at NeurIPS'19. Jinsung Yoon, Daniel Jarrett

README This project provides a rule learning algorithm for the deduction of syndrome definitions from time series data. Large parts of the algorithm a

Web Scraping, Document Deduplication & GPT-2 Fine-tuning with a newly created scam dataset.

Environment Inference for Invariant Learning This code accompanies the paper Environment Inference for Invariant Learning, which appears at ICML 2021.

Hierarchical GAN for large dimensional financial market data Implementation This repository is an implementation of the [Hierarchical (Sig-Wasserstein

MaD GUI Machine Learning and Data Analytics Graphical User Interface MaD GUI is a basis for graphical annotation and computational analysis of time se

PSML: A Multi-scale Time-series Dataset for Machine Learning in Decarbonized Energy Grids The electric grid is a key enabling infrastructure for the a

Dynamical Wasserstein Barycenters for Time Series Modeling This is the code related for the Dynamical Wasserstein Barycenter model published in Neurip

TCube: Domain-Agnostic Neural Time series Narration This repository contains the code for the paper: "TCube: Domain-Agnostic Neural Time series Narrat

Graph-Guided Network For Irregularly Sampled Multivariate Time Series Overview This repository contains processed datasets and implementation code for

Unified-EPT Code for the ICCV 2021 Workshop paper: A Unified Efficient Pyramid Transformer for Semantic Segmentation. Installation Linux, CUDA=10.0,

poutyne-transformers Train 🤗 -transformers models with Poutyne. Installation pip install poutyne-transformers Example import torch from transformers

Python Client and Toolkit for DataFrames, Big Data, Machine Learning and ETL in Elasticsearch

This repository contains code to containerize and deploy a GPU docker on AWS for summarization task. Find a detailed blogpost here Youtube Video Versi

Analysis of Virtualization-based Obfuscation This repository contains slides, samples and code of the 4h code deobfuscation workshop at r2con2021. We

Transformers4Rec is a flexible and efficient library for sequential and session-based recommendation, available for both PyTorch and Tensorflow.

IGMTF The source code and data of the paper "Instance-wise Graph-based Framework for Multivariate Time Series Forecasting". Requirements The framework

Brain Tokyo Workshop 🧠 🗼 This repo contains research materials released by members of the Google Brain team in Tokyo. Past Projects Weight Agnostic

Merlion: A Machine Learning Library for Time Series Table of Contents Introduction Installation Documentation Getting Started Anomaly Detection Foreca

Domino Research This repo contains projects under active development by the Domino R&D team. We build tools that help Data Scientists and ML engineers

BERT Got a Date: Introducing Transformers to Temporal Tagging Satya Almasian*, Dennis Aumiller*, and Michael Gertz Heidelberg University Contact us vi

2017 VQA Challenge Winner (CVPR'17 Workshop) pytorch implementation of Tips and Tricks for Visual Question Answering: Learnings from the 2017 Challeng

Merlion is a Python library for time series intelligence. It provides an end-to-end machine learning framework that includes loading and transforming data, building and training models, post-processing model outputs, and evaluating model performance. I

Transformers4Rec is a flexible and efficient library for sequential and session-based recommendation, available for both PyTorch and Tensorflow.

SCINet This is the original PyTorch implementation of the following work: Time Series is a Special Sequence: Forecasting with Sample Convolution and I

Markovflow Documentation | Tutorials | API reference | Slack What does Markovflow do? Markovflow is a Python library for time-series analysis via prob

Wav2Vec2CTC With KenLM Using KenLM ARPA language model with beam search to decode audio files and show the most probable transcription. Assuming you'v

NaLCoS - NAtural Language COmmit Search Search commit messages in your repository in natural language. NaLCoS (NAtural Language COmmit Search) is a co

Python Mini Projects A collection of easy Python small projects to help you improve your programming skills. Table Of Contents Aim Of The Project Cont

Fibonacci-Series-using-python Here, I find the Fibonacci Series using python Requirements No Special Requirements Contribution I have strong belief on

carbon-footprint-calculator Conda distribution ~/anaconda3/bin/conda install anaconda-client conda-build ~/anaconda3/bin/conda config --set anaconda_u

time-series-kafka-demo Mock stream producer for time series data using Kafka. I walk through this tutorial and others here on GitHub and on my Medium

CommentGeneration Code for lyric-section-to-comment generation based on huggingface transformers. Migrate Guyu model and code (both 12-layers and 24-l

Smahat allows to encode a sequence of integer values using a fixed (for all values) number of bits but minimal with regards to the data range. For example: for a series of boolean values only one bit is needed, for a series of integer percentages 7 bits are needed, etc.

Project Setup Follow the steps below to set up the project on your environment. Local Development Create a virtual environment with Python 3.7 or high

Example of animated maps in matplotlib + geopandas using entire time series of congressional district maps from UCLA archive. rendered, interactive version below

NFRipper2.0 I could not shared all the code here Because its has lots of files inisde it https://new.gdtot.me/file/86651844 - Downoad File From Here.

Pretrain and Fine-tune a T5 model with Flax on GCP This tutorial details how pretrain and fine-tune a FlaxT5 model from HuggingFace using a TPU VM ava

DALL-E-Tokenizer Huggingface package for the discrete VAE used for DALL-E.

Scenario: The Mutt Matcher (IoT version) According to the World Health Organization there are more than 200 million stray dogs worldwide. The American

Workshop Python UNSIKA 2021 Materi workshop "Light up your Python!" Himpunan Mahasiswa Sistem Informasi Fakultas Ilmu Komputer Universitas Singaperban

wxee What is wxee? wxee was built to make processing gridded, mesoscale time series weather and climate data quick and easy by integrating the data ca

ETNA is an easy-to-use time series forecasting framework. It includes built in toolkits for time series preprocessing, feature generation, a variety of predictive models with unified interface - from classic machine learning to SOTA neural networks, models combination methods and smart backtesting. ETNA is designed to make working with time series simple, productive, and fun.

2017 VQA Challenge Winner (CVPR'17 Workshop) pytorch implementation of Tips and Tricks for Visual Question Answering: Learnings from the 2017 Challeng

Simple tool/toolkit for evaluating NLG (Natural Language Generation) offering various automated metrics. Jury offers a smooth and easy-to-use interface. It uses datasets for underlying metric computation, and hence adding custom metric is easy as adopting datasets.Metric.

A pytorch easy re-implement of "YOLOX: Exceeding YOLO Series in 2021" 1. Notes This is a pytorch easy re-implement of "YOLOX: Exceeding YOLO Series in

Data Augmentation for Scene Text Recognition (ICCV 2021 Workshop) (Pronounced as "strog") Paper Arxiv Why it matters? Scene Text Recognition (STR) req

Framework overview This library allows to quickly implement different architectures based on Reservoir Computing (the family of approaches popularized

Gorilla Time Series Compression This is an implementation (with some adaptations) of the compression algorithm described in section 4.1 (Time series c

Query Selector Here you can find code and data loaders for the paper https://arxiv.org/pdf/2107.08687v1.pdf . Query Selector is a novel approach to sp

The tl;dr on a few notable transformer/language model papers + other papers (alignment, memorization, etc).

New State-of-the-Art in Preposition Sense Disambiguation Supervisor: Prof. Dr. Alexander Mehler Alexander Henlein Institutions: Goethe University TTLa

transformer-slt This repository gathers data and code supporting the experiments in the paper Better Sign Language Translation with STMC-Transformer.

TadGAN: Time Series Anomaly Detection Using Generative Adversarial Networks This is a Python3 / Pytorch implementation of TadGAN paper. The associated

AntiderivativeEstimator Program that estimates antiderivatives utilising Maclaurin series. Setup: Needs Python 3 and Git installed and added to PATH.

eexarray A Python interface between Earth Engine and xarray Description eexarray was built to make processing gridded, mesoscale time series data quic

UnICORNN (Undamped Independent Controlled Oscillatory RNN) [ICML 2021] This repository contains the implementation to reproduce the numerical experime

Voice2Series-Reprogramming Voice2Series: Reprogramming Acoustic Models for Time Series Classification International Conference on Machine Learning (IC

RoBERTa base model for Marathi Language (मराठी भाषा) Pretrained model on Marathi language using a masked language modeling (MLM) objective. RoBERTa wa

USAD - UnSupervised Anomaly Detection on multivariate time series Scripts and utility programs for implementing the USAD architecture. Implementation

spacy-huggingface-hub: Push your spaCy pipelines to the Hugging Face Hub This package provides a CLI command for uploading any trained spaCy pipeline

Time Series Research with Torch 这个开源项目主要是对经典的时间序列预测算法论文进行复现，模型主要参考自GluonTS，框架主要参考自Informer。 建立原因 相较于mxnet和TF，Torch框架中的神经网络层需要提前指定输入维度： # 建立线性层 TensorF

Dual Self-Attention Network for Multivariate Time Series Forecasting 20.10.26 Update: Due to the difficulty of installation and code maintenance cause

TS2Vec This repository contains the official implementation for the paper Learning Timestamp-Level Representations for Time Series with Hierarchical C

adapter-transformers A friendly fork of HuggingFace's Transformers, adding Adapters to PyTorch language models adapter-transformers is an extension of

A data preprocessing package for time series data. Design for machine learning and deep learning.

Extrair informações da internet de forma automatizada. Existem diversas maneiras de fazer isso, nesse tutorial vamos ver algumas delas, por meio de bibliotecas de python.

Soft DTW Loss Function for PyTorch in CUDA This is a Pytorch Implementation of Soft-DTW: a Differentiable Loss Function for Time-Series which is batch

pysesame3 Unofficial Python Library to communicate with SESAME 3 series products from CANDY HOUSE, Inc. This project aims to control SESAME 3 series d

tsflex is a toolkit for flexible time-series processing & feature extraction, making few assumptions about input data. Useful links Documentation Exam

A python library for easy manipulation and forecasting of time series.

Kats, a kit to analyze time series data, a lightweight, easy-to-use, generalizable, and extendable framework to perform time series analysis, from understanding the key statistics and characteristics, detecting change points and anomalies, to forecasting future trends.

MOT Tracked object bounding box association (CenterTrack++) New association method based on CenterTrack. Two new branches (Tracked Size and IOU) are a

Granger causality discovery for neural networks.

Clairvoyance: A Pipeline Toolkit for Medical Time Series Authors: van der Schaar Lab This repository contains implementations of Clairvoyance: A Pipel

TSForecasting This repository contains the implementations related to the experiments of a set of publicly available datasets that are used in the tim

neurodsp is a collection of approaches for applying digital signal processing to neural time series, including algorithms that have been proposed for the analysis of neural time series. It also includes simulation tools for generating plausible simulations of neural time series.

Microsoft contributing libraries, tools, recipes, sample codes and workshop contents for machine learning & deep learning.

Nested-Co-teaching (L2ID@CVPR2021) Pytorch implementation of paper "Boosting Co-teaching with Compression Regularization for Label Noise" [PDF] If our

Time series Timeseries Deep Learning Pytorch fastai - State-of-the-art Deep Learning with Time Series and Sequences in Pytorch / fastai

ShineOn: Illuminating Design Choices for Practical Video-based Virtual Clothing Try-on [ Paper ] [ Project Page ] This repository contains the code fo

QuickAI is a Python library that makes it extremely easy to experiment with state-of-the-art Machine Learning models.

QuickAI is a Python library that makes it extremely easy to experiment with state-of-the-art Machine Learning models.

AICITY2021_Track2_DMT The 1st place solution of track2 (Vehicle Re-Identification) in the NVIDIA AI City Challenge at CVPR 2021 Workshop. Introduction

sankee Visualize changes in classified time series data with interactive Sankey plots in Google Earth Engine Contents Description Installation Using P

Stock Market Buy/Sell/Hold prediction Using convolutional Neural Network This repo is an attempt to implement the research paper titled "Algorithmic F

We are a group of like-minded people trying to make access to weather data in Python feel like a warm summer breeze, similar to other projects like rdwd for the R language, which originally drew our interest in this project.

Multidimensional LSTM BitCoin Time Series Using multidimensional LSTM neural networks to create a forecast for Bitcoin price. For notes around this co

...Minimizing the mean square error on future experience. - Richard S. Sutton BTGym Scalable event-driven RL-friendly backtesting library. Build on

geextract Google Earth Engine data extraction tool. Quickly obtain Landsat multispectral time-series for exploratory analysis and algorithm testing On

thunder scalable analysis of image and time series analysis in python Thunder is an ecosystem of tools for the analysis of image and time series data