Bianace Prediction Pytorch Model

Related tags

Deep Learningbinance_prediction_pytorch
Overview

Bianace Prediction Pytorch Model

Main Results

ETHUSDT from 2021-01-01 00:00:00 to 2021-12-01 00:00:00

Time interval ROI
1d (Human) 2.74%
1d (Model) 125.05%
4h (Human) 36.86%
4h (Model) 300.37%
1h (Human) 37.55%
1h (Model) 393.66%

BTCUSDT from 2021-01-01 00:00:00 to 2021-12-01 00:00:00

Time interval ROI
1d (Human) 3.11%
1d (Model) 30.08%
4h (Human) 18.30%
4h (Model) 30.67%
1h (Human) 19.79%
1h (Model) 32.07%

Getting started

Environment

  • Test OS: Ubuntu 16.04 LTS
  • Python version: 3.8

Preparation

  • Create folders.
mkdir images
mkdir checkpoints
  • Please run pip install –r requirements.txt to install the needed libraries.

Dataset

Binance Public Data

  • Clone the repo.
  • Follow the instruction to download required data.
# ETHUSDT
python download-kline.py -s ETHUSDT -startDate 2017-08-01 -endDate 2021-12-01

# BTCUSDT
python download-kline.py -s BTCUSDT -startDate 2017-08-01 -endDate 2021-12-01
  • It will download the required data as below. Unzip the zip files under the 1h, 4h and 1d directories.
binance_prediction_pytorch
    `-- binance-public-data
        `-- data
            `-- data
                `-- spot
                    |-- daily
                    `-- monthly
                        `-- klines
                            |-- ETHUSDT
                            `-- BTCUSDT
  • Then soft link the data directory to the repo root as below.
binance_prediction_pytorch
    |-- binance-public-data
    `-- data
        `-- spot
            |-- daily
            `-- monthly
                `-- klines
                    |-- ETHUSDT
                    `-- BTCUSDT

Experiments

Training

  • Run training and evaluation on ETHUSDT. It will store the checkpoints under checkpoints with ticker name and time interval if don't specify the checkpoint path with --ckpt.
# 1d
./run.sh ETHUSDT 1d

# 4h
./run.sh ETHUSDT 4h --sell_rate 0.03

# 1h
./run.sh ETHUSDT 1h --sell_rate 0.03
  • Run training and evaluation on BTCUSDT
# 1d
./run.sh BTCUSDT 1d

# 4h
./run.sh BTCUSDT 4h --sell_rate 0.03

# 1h
./run.sh BTCUSDT 1h --sell_rate 0.03

Inference

  • Specify the checkpoint path with eval mode to only do the inference.
./run.sh ETHUSDT 1h --sell_rate 0.03 --ckpt ${YOUR_CHECKPOINT_PATH} --eval
Owner
RoyYang
M.S. student @ VSLab
RoyYang
GitHub Repository
Embodied Intelligence via Learning and Evolution

Embodied Intelligence via Learning and Evolution This is the code for the paper Embodied Intelligence via Learning and Evolution Agrim Gupta, Silvio S

Agrim Gupta 111 Dec 13, 2022
This is a student data management application developed in Python and TKinter. It utilizes the TKinter pillow library to include images to buttons. I've separated TKinter elements into their own individual classes. The user can change the smilely face color for each button individually or by entire row.

Smiley Face Cube Display Table of Contents Project Description Getting Started Prerequisites Installation & Deployment Additional Documentation Projec

Yohan (John) Cho 0 Aug 04, 2021
Deep Q-learning for playing chrome dino game

[PYTORCH] Deep Q-learning for playing Chrome Dino

Viet Nguyen 68 Dec 05, 2022
CTRL-C: Camera calibration TRansformer with Line-Classification

CTRL-C: Camera calibration TRansformer with Line-Classification This repository contains the official code and pretrained models for CTRL-C (Camera ca

57 Nov 14, 2022
Forest R-CNN: Large-Vocabulary Long-Tailed Object Detection and Instance Segmentation (ACM MM 2020)

Forest R-CNN: Large-Vocabulary Long-Tailed Object Detection and Instance Segmentation (ACM MM 2020) Official implementation of: Forest R-CNN: Large-Vo

Jialian Wu 54 Jan 06, 2023
Migration of Edge-based Distributed Federated Learning

FedFly: Towards Migration in Edge-based Distributed Federated Learning About the research Due to mobility, a device participating in Federated Learnin

qub-blesson 11 Nov 13, 2022
Deep Learning Interviews book: Hundreds of fully solved job interview questions from a wide range of key topics in AI.

This book was written for you: an aspiring data scientist with a quantitative background, facing down the gauntlet of the interview process in an increasingly competitive field. For most of you, the

4.1k Dec 28, 2022
Official repository for the paper "Instance-Conditioned GAN"

Official repository for the paper "Instance-Conditioned GAN" by Arantxa Casanova, Marlene Careil, Jakob Verbeek, Michał Drożdżal, Adriana Romero-Soriano.

Facebook Research 510 Dec 30, 2022
Data visualization app for H&M competition in kaggle

handm_data_visualize_app Data visualization app by streamlit for H&M competition in kaggle. competition page: https://www.kaggle.com/competitions/h-an

Kyohei Uto 12 Apr 30, 2022
UFPR-ADMR-v2 Dataset

UFPR-ADMR-v2 Dataset The UFPR-ADMRv2 dataset contains 5,000 dial meter images obtained on-site by employees of the Energy Company of Paraná (Copel), w

Gabriel Salomon 8 Sep 29, 2022
QilingLab challenge writeup

qiling lab writeup shielder 在 2021/7/21 發布了 QilingLab 來幫助學習 qiling framwork 的用法，剛好最近有用到，順手解了一下並寫了一下 writeup。 前情提要 Qiling 是一款功能強大的模擬框架，和 qemu user mode

Yuan 17 Nov 17, 2022
Official Pytorch implementation of "CLIPstyler:Image Style Transfer with a Single Text Condition"

CLIPstyler Official Pytorch implementation of "CLIPstyler:Image Style Transfer with a Single Text Condition" Environment Pytorch 1.7.1, Python 3.6 $ c

201 Dec 29, 2022
Modifications of the official PyTorch implementation of StyleGAN3. Let's easily generate images and videos with StyleGAN2/2-ADA/3!

Alias-Free Generative Adversarial Networks (StyleGAN3) Official PyTorch implementation of the NeurIPS 2021 paper Alias-Free Generative Adversarial Net

Diego Porres 185 Dec 24, 2022
Jittor is a high-performance deep learning framework based on JIT compiling and meta-operators.

Jittor: a Just-in-time(JIT) deep learning framework Quickstart | Install | Tutorial | Chinese Jittor is a high-performance deep learning framework bas

2.7k Jan 03, 2023
Multispectral Object Detection with Yolov5

Multispectral-Object-Detection Intro Official Code for Cross-Modality Fusion Transformer for Multispectral Object Detection. Multispectral Object Dete

Richard Fang 121 Jan 01, 2023
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

Marco Cerliani 422 Jan 08, 2023
Differentiable molecular simulation of proteins with a coarse-grained potential

Differentiable molecular simulation of proteins with a coarse-grained potential This repository contains the learned potential, simulation scripts and

UCL Bioinformatics Group 44 Dec 10, 2022
Re-TACRED: Addressing Shortcomings of the TACRED Dataset

Re-TACRED Re-TACRED: Addressing Shortcomings of the TACRED Dataset

George Stoica 40 Dec 10, 2022
Double pendulum simulator using a symplectic Euler's method and Hamiltonian mechanics

Symplectic Double Pendulum Simulator Double pendulum simulator using a symplectic Euler's method. The program calculates the momentum and position of

Scott Marino 1 Jan 12, 2022
Train robotic agents to learn pick and place with deep learning for vision-based manipulation in PyBullet.

Ravens is a collection of simulated tasks in PyBullet for learning vision-based robotic manipulation, with emphasis on pick and place. It features a Gym-like API with 10 tabletop rearrangement tasks,

Google Research 367 Jan 09, 2023