lovelife94

lovelife94's Stars

• Kevin-Vivas/Digital_Modulation_Py

  Welcome to the Digital_Modulation_Py repository! This repository provides digital modulation techniques, including QPSK,PSK and QAM,using Python.

  Language:Python92

• zh320/realtime-semantic-segmentation-pytorch

  PyTorch implementation of over 30 realtime semantic segmentations models, e.g. BiSeNetv1, BiSeNetv2, CGNet, ContextNet, DABNet, DDRNet, EDANet, ENet, ERFNet, ESPNet, ESPNetv2, FastSCNN, ICNet, LEDNet, LinkNet, PP-LiteSeg, SegNet, ShelfNet, STDC, SwiftNet, and support knowledge distillation, distributed training etc.

  Language:Python8115

• google-research/tuning_playbook

  A playbook for systematically maximizing the performance of deep learning models.

  26k2.2k

• jahongir7174/EfficientViTSAM-onnx

  EfficientViTSAM inference using ONNXRuntime

  Language:Python3

• idancz/Gigantic_MuMIMO_ViterbiBasedNet

  Deep Neural Networks receivers based Viterbi algorithm for Maximum Likelihood priors-learning in digital communication

  Language:Jupyter Notebook9

• sanjeevnara7/FootballPassPrediction

  Football/Soccer Pass Receiver Prediction using Object Detection/Graph Neural Networks (GNNs)

  Language:Jupyter Notebook181

• PaddlePaddle/PaddleSpatial

  PaddleSpatial is an open-source spatial-temporal computing tool based on PaddlePaddle.

  Language:GLSL325164

• PaddlePaddle/PGL

  Paddle Graph Learning (PGL) is an efficient and flexible graph learning framework based on PaddlePaddle

  Language:Python1.6k311

• philipperemy/n-beats

  Keras/Pytorch implementation of N-BEATS: Neural basis expansion analysis for interpretable time series forecasting.

  Language:Python852165

• thuml/Koopa

  Code release for "Koopa: Learning Non-stationary Time Series Dynamics with Koopman Predictors" (NeurIPS 2023), https://arxiv.org/abs/2305.18803

  Language:Python16920

• salesforce/Merlion

  Merlion: A Machine Learning Framework for Time Series Intelligence

  Language:Python3.3k292

• dask/dask

  Parallel computing with task scheduling

  Language:Python12.3k1.7k

• githubnext/monaspace

  An innovative superfamily of fonts for code

  Language:TypeScript13.3k219

• romanmichaelpaolucci/Q-Fin

  A Python library for mathematical finance

  Language:Python39052

• vi3k6i5/flashtext

  Extract Keywords from sentence or Replace keywords in sentences.

  Language:Python5.6k599

• gto76/python-cheatsheet

  Comprehensive Python Cheatsheet

  Language:Python35.9k6.4k

• aosabook/500lines

  500 Lines or Less

  Language:JavaScript29.2k5.9k

• albumentations-team/albumentations

  Fast and flexible image augmentation library. Paper about the library: https://www.mdpi.com/2078-2489/11/2/125

  Language:Python13.8k1.6k

• arnabbiswas1/kaggle_pipeline_tps_aug_22

  Kaggle Pipeline for tabular data competitions

  Language:Jupyter Notebook20522

• PacktPublishing/The-Kaggle-Book

  Code Repository for The Kaggle Book, Published by Packt Publishing

  Language:Jupyter Notebook2.1k450

• microsoft/qlib

  Qlib is an AI-oriented quantitative investment platform that aims to realize the potential, empower research, and create value using AI technologies in quantitative investment, from exploring ideas to implementing productions. Qlib supports diverse machine learning modeling paradigms. including supervised learning, market dynamics modeling, and RL.

  Language:Python14.7k2.6k

• microprediction/microprediction

  If you can measure it, consider it predicted

  Language:Jupyter Notebook32158

• erdogant/bnlearn

  Python library for learning the graphical structure of Bayesian networks, parameter learning, inference and sampling methods.

  Language:Jupyter Notebook46245

• stanek-fi/rank_optimization

  replication repository for the article A Note on the M6 Forecasting Competition: Rank Optimization

  Language:PostScript2

• wanaflah/m6-competition

  Language:Jupyter Notebook1

• paciops/M6-Competition

  1

• rizal-mujahiddan/m6_competition

  Language:HTML1

• aleksei-mashlakov/m6_competition

  Source code for AM Naive team in M6 Forecasting Competition

  Language:Jupyter Notebook21

• sebrad/M6

  M6 Competition - 3rd Place Solution for the Forecasting Track

  Language:R1

• edu230991/m6-competition

  Repository for participating to the M6 competition

  Language:Jupyter Notebook1