Python Attention-CLX-stock-prediction Resources

GAT - Graph Attention Network (PyTorch) 💻 + graphs + 📣 = ❤️ This repo contains a PyTorch implementation of the original GAT paper ( 🔗 Veličković et

Deep Learning Time Series Forecasting List of state of the art papers focus on deep learning and resources, code and experiments using deep learning f

Fast convergence of detr with spatially modulated co-attention Usage There are no extra compiled components in SMCA DETR and package dependencies are

SCOUTER: Slot Attention-based Classifier for Explainable Image Recognition PDF Abstract Explainable artificial intelligence has been gaining attention

Generating Smooth Pose Sequences for Diverse Human Motion Prediction This is official implementation for the paper Generating Smooth Pose Sequences fo

Block Sparse Attention 研究总结 本人近半年来对Block Sparse Attention（块稀疏注意力）的研究总结（持续更新中）。按时间顺序，主要分为如下三部分： PyTorch 自定义 CUDA 算子——以矩阵乘法为例 基于 Triton 的 Block Sparse A

🚀 Pancakeswap BSC Sniper Bot 🚀 Web3 Pancakeswap Sniper && Take Profit/StopLose bot written in python3, Please note the license conditions! The secon

Attention-based Transformation from Latent Features to Point Clouds This repository contains a PyTorch implementation of the paper: Attention-based Tr

Predico Disease Prediction system based on symptoms provided by patient- using Python-Django & Machine Learning

neural_network_for_stock_price_prediction Neural networks for stock price predic

bottom-up-attention This code implements a bottom-up attention model, based on multi-gpu training of Faster R-CNN with ResNet-101, using object and at

IRON Kaggle project done while doing IRONHACK Bootcamp where we had to analyze and use a Machine Learning Project to predict future sales. In this case, we ended up using XGBoost because it was the one with a higher score and less overfitting.

Iris Species Predictor Iris prediction is used to classify iris species using their sepal length, sepal width, petal length and petal width created us

High-Low Stock trading bot made using the Robinhood API / Python library... Index Installation Use Development Notes Installation To Install and run t

This file contains the following documents sumbited for Baruch CIS9665 group 9 fall 2021. 1. Dataset: drug_reviews.csv 2. python codes for text classi

StockAnalysisApp A stock analysis app with streamlit. You select the ticker of the stock and the app makes a series of analysis by using the price cha

Pancakeswap Sniper Bot GUI Uniswap Matic 2022 (WINDOWS LINUX MAC) ⭐️ AUTO BUY TOKEN ON LAUNCH AFTER ADD LIQUIDITY ⭐️ ⭐️ First GUI SNIPER BOT for WINDO

Detection of Fake Reviews on Online Review Platforms using Deep Learning Architectures Dataset: https://s3.amazonaws.com/fast-ai-nlp/yelp_review_polar

Motion prediction with Hierarchical Motion Recurrent Network Introduction This work concerns motion prediction of articulate objects such as human, fi

SAFL: A Self-Attention Scene Text Recognizer with Focal Loss This repository implements the SAFL in pytorch. Installation conda env create -f environm

cluster-link-prediction This repository provides some of the code implemented and the data used for the work proposed in "A Cluster-Based Trip Predict

Contents Semantic Image Synthesis with DAGAN Installation Dataset Preparation Generating Images Using Pretrained Model Train and Test New Models Evalu

AttentionGAN-v2 for Unpaired Image-to-Image Translation AttentionGAN-v2 Framework The proposed generator learns both foreground and background attenti

connect-caption-and-trace This repository contains the reference code for our paper Connecting What to Say With Where to Look by Modeling Human Attent

Introduction This repository is for X-Linear Attention Networks for Image Captioning (CVPR 2020). The original paper can be found here. Please cite wi

Adaptively Aligned Image Captioning via Adaptive Attention Time This repository includes the implementation for Adaptively Aligned Image Captioning vi

A data pipeline consisting of an AWS lambda function reading data from yfinance API, an AWS Kinesis stream to receive & store data in S3 buckets and AWS Glue crawler & Athena to run SQL queries.

SA-tensorflow Tensorflow implementation of soft-attention mechanism for video caption generation. An example of soft-attention mechanism. The attentio

Show, Attend and Tell Update (December 2, 2016) TensorFlow implementation of Show, Attend and Tell: Neural Image Caption Generation with Visual Attent

Introduction This neural system for image captioning is roughly based on the paper "Show, Attend and Tell: Neural Image Caption Generation with Visual

COVID Predictions This repo contains ML models to be trained on COVID-19 data from the UK, sourced off of Kaggle here. This uses many different ML mod

Channel-Wise Attention-Based Network for Self-Supervised Monocular Depth Estimation This is the official implementation for the method described in Ch

NFT-Price-Prediction-CNN - Using visual feature extraction, prices of NFTs are predicted via CNN (Alexnet and Resnet) architectures.

FaceAPI AI-powered Face Detection & Rotation Tracking, Face Description & Recognition, Age & Gender & Emotion Prediction for Browser and NodeJS using

Churn-Prediction-Project In this project, a churn prediction model is developed for a private bank as a term project for Data Mining class. Project in

Relating-Social-Media-to-Stock-Movement-Public - We explore the application of Machine Learning for predicting the return of the stock by using the information of stock returns. A trading strategy based on this analysis leads to increased trading profits up to three times compared with a simple buy and hold strategy.

stroke-predictions-ml-model machine learning model to predict individuals chance

AlexaUsingPython - Alexa will pay attention to your order, as: Hello Alexa, play music, Hello Alexa, what's the time? Alexa will pay attention to your order, get it, and afterward do some activity as indicated by your order.

A collection of graph classification methods, covering embedding, deep learning, graph kernel and factorization papers

TensorFlow 101: Introduction to Deep Learning I have worked all my life in Machine Learning, and I've never seen one algorithm knock over its benchmar

How-to-Predict-Stock-Prices-Easily-Demo How to Predict Stock Prices Easily - Intro to Deep Learning #7 by Siraj Raval on Youtube ##Overview This is th

[UPDATED] A TensorFlow Implementation of Attention Is All You Need When I opened this repository in 2017, there was no official code yet. I tried to i

Flight_fare-Prediction It is a Flight_fare Prediction Web Application Using Machine learning,Python and flask Using Machine leaning i have created a F

Stock History Display Available on Heroku: https://stock-history-display.herokua

Mortgage-loan-prediction - Show how to perform advanced Analytics and Machine Learning in Python using a full complement of PyData utilities. This is aimed at those looking to get into the field of Data Science or those who are already in the field and looking to solve a real-world project with python.

Price-Prediction-For-a-Dream-Home ROADMAP TO THIS LINEAR REGRESSION BASED HOUSE PRICE PREDICTION PREDICTION MODEL Import all the dependencies of the p

Stock Price Prediction Using Deep Learning Univariate Time Series Predicting stock price using historical data of a company using Neural networks for

Mortgage-loan-prediction - Show how to perform advanced Analytics and Machine Learning in Python using a full complement of PyData utilities

Medical-Insurance-Cost-Prediction-using-Machine-learning - Here in this project, I will use regression analysis to predict medical insurance cost for people in different regions, and based on several aspects like : Smoking, Number of children, BMI...etc.

AirQualityPredictionUsingLSTM In this Repo, i present to you the winning solution of smart gujarat hackathon 2019 where the task was to predict the qu

Shunted Transformer This is the offical implementation of Shunted Self-Attention via Multi-Scale Token Aggregation by Sucheng Ren, Daquan Zhou, Shengf

SEAM The implementation of Self-supervised Equivariant Attention Mechanism for Weakly Supervised Semantic Segmentaion. You can also download the repos

CCGL: Contrastive Cascade Graph Learning This repo provides a reference implementation of Contrastive Cascade Graph Learning (CCGL) framework as descr

Beibo is a Python library that uses several AI prediction models to predict stocks returns over a defined period of time.

SelfGNN A PyTorch implementation of "SelfGNN: Self-supervised Graph Neural Networks without explicit negative sampling" paper, which will appear in Th

Bianace Prediction Pytorch Model Main Results ETHUSDT from 2021-01-01 00:00:00 t

Python Portfolio Analytics A portfolio tracker featuring account transactions, historical allocation, dividends and splits management and endless perf

nfelo nfelo is a power ranking, prediction, and betting model for the NFL. Nfelo take's 538's Elo framework and further adapts it for the NFL, hence t

The following Python scripts aim to use a Random Forest machine learning algorithm to predict the water affinity of Metal-Organic Frameworks (MOFs). The training set is extracted from the Cambridge Structural Database and the CoRE_MOF 2019 dataset.

Graph-Bert Source code of "Graph-Bert: Only Attention is Needed for Learning Graph Representations". Please check the script.py as the entry point. We

Video_Pace This repository contains the code for the following paper: Jiangliu Wang, Jianbo Jiao and Yunhui Liu, "Self-Supervised Video Representation

SfMLearner This codebase implements the system described in the paper: Unsupervised Learning of Depth and Ego-Motion from Video Tinghui Zhou, Matthew

[TensorFlow 2] Attention is all you need (Transformer) TensorFlow implementation of "Attention is all you need (Transformer)" Dataset The MNIST datase

SAG-DTA The code is the implementation for the paper 'SAG-DTA: Prediction of Drug–Target Affinity Using Self-Attention Graph Network'. Requirements py

XViT - Space-time Mixing Attention for Video Transformer This is the official implementation of the XViT paper: @inproceedings{bulat2021space, title

Attention for PyTorch with Linear Memory Footprint Unofficially implements https://arxiv.org/abs/2112.05682 to get Linear Memory Cost on Attention (+

ALiBi PyTorch implementation of Train Short, Test Long: Attention with Linear Biases Enables Input Length Extrapolation. Quickstart Clone this reposit

Hierarchical Attention Mining (HAM) for weakly-supervised abnormality localization This is the official PyTorch implementation for the HAM method. Pap

Multi-Probe Attention for Semantic Indexing About This project is developed for the topic of COVID-19 semantic indexing. Directories & files A. The di

memory_efficient_attention.pytorch A human-readable PyTorch implementation of "Self-attention Does Not Need O(n^2) Memory" (Rabe&Staats'21). def effic

Weak-supervised Visual Geo-localization via Attention-based Knowledge Distillation Introduction WAKD is a PyTorch implementation for our ICPR-2022 pap

ttslearn: Library for Pythonで学ぶ音声合成 (Text-to-speech with Python) 日本語は以下に続きます (Japanese follows) English: This book is written in Japanese and primaril

D-HAN The source code of D-HAN This is the source code of D-HAN: Dynamic News Recommendation with Hierarchical Attention Network. However, only the co

AKShare is an elegant and simple financial data interface library for Python, built for human beings

DSAMNet The pytorch implementation for "A Deeply-supervised Attention Metric-based Network and an Open Aerial Image Dataset for Remote Sensing Change

Multimodal Trajectory Prediction Conditioned on Lane-Graph Traversals This repository contains code for "Multimodal trajectory prediction conditioned

CoANet: Connectivity Attention Network for Road Extraction From Satellite Imagery This paper (CoANet) has been published in IEEE TIP 2021. This code i

Locally-Shifted-Attention-With-Early-Global-Integration Pretrained models You can download all the models from here. Training Imagenet python -m torch

A-ESRGAN: Training Real-World Blind Super-Resolution with Attention-based U-net Discriminators The authors are hidden for the purpose of double blind

Tensorflow Implementation for "Pre-trained Deep Convolution Neural Network Model With Attention for Speech Emotion Recognition" Pre-trained Deep Convo

Naive-Bayes Predict Breast Cancer Wisconsin (Diagnostic) using Naive Bayes Downloading Data Set Use our Breast Cancer Wisconsin Data Set Also you can

frugally-deep Use Keras models in C++ with ease Table of contents Introduction Usage Performance Requirements and Installation FAQ Introduction Would

Show, Attend and Tell Update (December 2, 2016) TensorFlow implementation of Show, Attend and Tell: Neural Image Caption Generation with Visual Attent

SelectionGAN for Guided Image-to-Image Translation CVPR Paper | Extended Paper | Guided-I2I-Translation-Papers Citation If you use this code for your

Memory Efficient Attention This is unofficial implementation of Self-attention Does Not Need O(n^2) Memory for Jax and PyTorch. Implementation is almo

GAN-motion-Prediction An LSTM based GAN for motion synthesis has a few issues reading H3.6M data from A.Jain et al , will fix soon. Prediction of the

timemachines Autonomous, univariate, k-step ahead time-series forecasting functions assigned Elo ratings You can: Use some of the functionality of a s

Pose-Transfer Code for the paper Progressive Pose Attention for Person Image Generation in CVPR19(Oral). The paper is available here. Video generation

Movie-Success-Prediction A simple python program which predicts the success of a movie based on it's type, actor, actress and director. The program us

Label Studio for Hugging Face's Transformers Website • Docs • Twitter • Join Slack Community Transfer learning for NLP models by annotating your textu

Stock market bot that will be used to learn about API calls and database connections.

PUREPLES - Pure Python Library for ES-HyperNEAT About This is a library of evolutionary algorithms with a focus on neuroevolution, implemented in pure

GANformer: Generative Adversarial Transformers Drew A. Hudson* & C. Lawrence Zitnick Update: We released the new GANformer2 paper! *I wish to thank Ch

Edge-augmented Graph Transformer Introduction This is the official implementation of the Edge-augmented Graph Transformer (EGT) as described in https:

Nystromformer: A Nystrom-based Algorithm for Approximating Self-Attention April 6, 2021 We extended segment-means to compute landmarks without requiri

Sinkhorn Transformer This is a reproduction of the work outlined in Sparse Sinkhorn Attention, with additional enhancements. It includes a parameteriz

Pay Attention when Required (PAR) Transformer-XL An implementation of the Pay Attention when Required transformer from the paper: https://arxiv.org/pd

Routing Transformer A fully featured implementation of Routing Transformer. The paper proposes using k-means to route similar queries / keys into the

Linear Multihead Attention (Linformer) PyTorch Implementation of reproducing the Linear Multihead Attention introduced in Linformer paper (Linformer:

DeBERTa: Decoding-enhanced BERT with Disentangled Attention This repository is the official implementation of DeBERTa: Decoding-enhanced BERT with Dis