Code for How To Create A Fully Automated AI Based Trading System With Python

Last update: Jan 05, 2023

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Overview

AI Based Trading System

This code works as a boilerplate for an AI based trading system with yfinance as data source and RobinHood or Alpaca as brokers. DO NOT USE IT FOR TRADING AS IT IS. Follow the tutorial in Medium.

Since I plan to keep writing on this topic I'm moving the original boilerplate to the original_boilerplate folder - without removing anything. I'll keep the ai-trading-system folder polished and more production-ready.

Usage so far:

$ sudo dockerd
$ docker-compose up --build ai-trading-system

Stay tuned!

Owner

Rubén

Doin' it right

GitHub Repository

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Code for How To Create A Fully Automated AI Based Trading System With Python

Related tags

Overview

AI Based Trading System

Owner

Rubén

SPRING is a seq2seq model for Text-to-AMR and AMR-to-Text (AAAI2021).

Direct LiDAR Odometry: Fast Localization with Dense Point Clouds

RaftMLP: How Much Can Be Done Without Attention and with Less Spatial Locality?

This project aim to create multi-label classification annotation tool to boost annotation speed and make it more easier.

Steer OpenAI's Jukebox with Music Taggers

Code for IntraQ, PyTorch implementation of our paper under review

Code and models used in "MUSS Multilingual Unsupervised Sentence Simplification by Mining Paraphrases".

Interpretation of T cell states using reference single-cell atlases

The mini-MusicNet dataset

Code repo for "FASA: Feature Augmentation and Sampling Adaptation for Long-Tailed Instance Segmentation" (ICCV 2021)

This source code is implemented using keras library based on "Automatic ocular artifacts removal in EEG using deep learning"

Learning Dense Representations of Phrases at Scale (Lee et al., 2020)

Foreground-Action Consistency Network for Weakly Supervised Temporal Action Localization

Scrutinizing XAI with linear ground-truth data

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