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Deep-Probabilistic-Modelling-

Deep Probabilistic Modelling of Price Movements for High-Frequency Trading

Ai_Pdf_Reseach

Using LangChain to create a Streamlit web application for querying and analyzing content from a PDF document. The application allows users to input questions related to the PDF content, and it provides relevant answers along with additional analysis.

ai_readme_generator

AI Readme Generator reads any Git repository and suggests a README.md or a Pytest-based test file from the repository code, using Langchain and OpenAI GPT-4 or GPT-3.5-turbo.

AiTweet

Twitter Bot for Cannabis Industry Insights uses openAi API to generate crypto, cannabis and nft related content to twitter

aws-deployment-framework

The AWS Deployment Framework (ADF) is an extensive and flexible framework to manage and deploy resources across multiple AWS accounts and regions based on AWS Organizations.

binance-public-data

Details on how to get Binance public data

BTC_LTSM_Fear_Greed_Prediction

BTC_LTSM_Fear_Greed_Prediction

Bursa-Malaysia

buy-and-hold-vs-rsi

Compares the performance of a buy-and-hold strategy against a Relative Strength Index (RSI) based trading strategy using historical stock data from Yahoo Finance. The script analyzes the performance of these two strategies on Coca-Cola (KO) stock. Providing insights into their returns and risks.

CCXT-Algo-Generator

LangChain CCXT Code Generator and Deployment on Vercel is a project designed to simplify the process of creating cryptocurrency trading algorithms

deeplearning4j

Suite of tools for deploying and training deep learning models using the JVM. Highlights include model import for keras, tensorflow, and onnx/pytorch,

Financial-Machine_Learning

A curated list of practical financial machine learning tools and applications.

FXCM_ML

Implements a deep learning-based forex trading algorithm designed to make buy and sell decisions in financial markets based on historical price data and real-time streaming data

HFT_MM

HFT Market Making Model for Multiple Exchange Using CCXT

Interactive-Broker-SMA-Crossover

Trading On IKBR: SMA (Simple Moving Average) crossover. By analyzing the moving averages of asset prices, we can determine entry and exit points for our trades. The goal is to buy when the short-term moving average crosses above the long-term moving average and sell when the opposite occurs.

j4nt4n

to build something awesome

KLSE_LTSM_Autoencoder

This project uses historical data of Kuala Lumpur Stock Exchange to identify trade anomalies using LTSM

Kucoin_CryptoDataDownload

This Python script offers a streamlined solution for fetching historical data for cryptocurrencies traded on the KuCoin exchange, making it easier than ever to access the information you need to analyze market trends and make informed trading decisions.

Kucoin_Logistic_Regression

Yes, the code provided is suitable for use in a Jupyter Notebook environment. You can run this code cell by cell in your Jupyter Notebook just like any other Python code.

Limit_Pancake_GUI

it should be awesome for Pancakeswap automation

MEV-FRONTRUN-BOT-BSC

This MEV Front Run searches for large transactions in the BSC mempool using wss provider pending Promise

OBI_RFclassifier

Random Forest Classifier over Kucoin Futures Order Book Imbalance Data and RSI

rag-tutorial-v2

An Improved Langchain RAG Tutorial (v2) with local LLMs, database updates, and testing.

snekmate

State-of-the-art, highly opinionated, hyper-optimised, and secure 🐍Vyper smart contract building blocks.

Solana-Shitcoin-Analyzer

Analyse the token using the pair name or pair address

Stock-Prediction-LTSM

This project utilizes LSTM (Long Short-Term Memory) neural networks to predict stock prices for four different symbols: Apple (AAPL), Nvidia (NVDA), Google (GOOGL), and Amazon (AMZN). The LSTM models are trained using historical stock price data fetched from Yahoo Finance and evaluated based on various performance metrics.

SWE-agent

SWE-agent takes a GitHub issue and tries to automatically fix it, using GPT-4. It solves 12.29% of bugs in the SWE-bench evaluation set (comparable to Devin) and take just 1.5 minutes to run (7x faster than Devin).

vanilla-js-boilerplate

vanilla-js-boilerplate

yew_solana_daap

Utilizing Yew, a Rust framework for client-side web applications, the project constructs interactive and reactive components. Key components include `PhantomConnect`, managing the connection to the Phantom wallet, and various UI elements like buttons.

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