Pinned Repositories
3-min-pytorch
<펭귄브로의 3분 딥러닝, 파이토치맛> 예제 코드
AI-Strategies-StockMarket
App to test strategies based on artificial intelligence for investing in the stock market.
AjouStock
Stock trading project using Tensorflow(or Keras) with Python
algorithms
Minimal examples of data structures and algorithms in Python
Awesome-Quant-Machine-Learning-Trading
Quant/Algorithm trading resources with an emphasis on Machine Learning
BreezeStyleSheets
Breeze/BreezeDark-like Qt StyleSheets
Deep-Learning-Machine-Learning-Stock
Deep Learning and Machine Learning stocks represent a promising long-term or short-term opportunity for investors and traders.
examples
Learn to create a desktop app with Python and Qt
FinanceDataReader
Financial data reader
flask-dashboard-adminlte
AdminLTE Flask - Open-source Seed Project | AppSeed
jaehong-park-78's Repositories
jaehong-park-78/AI-Strategies-StockMarket
App to test strategies based on artificial intelligence for investing in the stock market.
jaehong-park-78/algorithms
Minimal examples of data structures and algorithms in Python
jaehong-park-78/Awesome-Quant-Machine-Learning-Trading
Quant/Algorithm trading resources with an emphasis on Machine Learning
jaehong-park-78/BreezeStyleSheets
Breeze/BreezeDark-like Qt StyleSheets
jaehong-park-78/Deep-Learning-Machine-Learning-Stock
Deep Learning and Machine Learning stocks represent a promising long-term or short-term opportunity for investors and traders.
jaehong-park-78/examples
Learn to create a desktop app with Python and Qt
jaehong-park-78/flask-dashboard-adminlte
AdminLTE Flask - Open-source Seed Project | AppSeed
jaehong-park-78/h0ack
jaehong-park-78/istocku
jaehong-park-78/machine-learning-for-trading
Code for Machine Learning for Algorithmic Trading, 2nd edition.
jaehong-park-78/main
jaehong-park-78/MapAssist
D2R MapHack
jaehong-park-78/newspaper
News, full-text, and article metadata extraction in Python 3. Advanced docs:
jaehong-park-78/OSGenome
An Open Source Web Application for Genetic Data (SNPs) using 23AndMe and Data Crawling Technologies
jaehong-park-78/pandas-ta
Technical Analysis Indicators - Pandas TA is an easy to use Python 3 Pandas Extension with 130+ Indicators
jaehong-park-78/pycaret
An open-source, low-code machine learning library in Python
jaehong-park-78/Python
All Algorithms implemented in Python
jaehong-park-78/python-algorithms
Collection of algorithm implementations from various sources plus own creations.
jaehong-park-78/qt-material
Material inspired stylesheet for PySide6, PySide2 and PyQt5
jaehong-park-78/qxresearch-event-1
Python hands on tutorial with 50+ Python Application (10 lines of code)
jaehong-park-78/SimpleStockAnalysisPython
Teaches step-by-step to analysis stock data in python.
jaehong-park-78/snpquery
jaehong-park-78/stock
jaehong-park-78/Stock-Prediction-Models
Gathers machine learning and deep learning models for Stock forecasting including trading bots and simulations
jaehong-park-78/Stock_Analysis_For_Quant
Different Types of Stock Analysis in Excel, Matlab, Power BI, Python, R, and Tableau
jaehong-park-78/stockpredictionai
In this noteboook I will create a complete process for predicting stock price movements. Follow along and we will achieve some pretty good results. For that purpose we will use a Generative Adversarial Network (GAN) with LSTM, a type of Recurrent Neural Network, as generator, and a Convolutional Neural Network, CNN, as a discriminator. We use LSTM for the obvious reason that we are trying to predict time series data. Why we use GAN and specifically CNN as a discriminator? That is a good question: there are special sections on that later.
jaehong-park-78/systrader
파이썬을 이용한 자동 주식투자 시스템
jaehong-park-78/ta
Technical Analysis Library using Pandas and Numpy
jaehong-park-78/trading-utils
Collection of scripts and utilities for stock market analysis, strategies etc
jaehong-park-78/Zerodha_Live_Automate_Trading-_using_AI_ML_on_Indian_stock_market
Online trading using Artificial Intelligence Machine leaning with python on Indian Stock Market, trading using live bots indicators screener and backtesters using rest api and websocket 😊