Pinned Repositories
AHKs
My AHK library
awesome-AutoHotkey
A curated list of awesome AutoHotkey libraries, library distributions, scripts, tools and resources.
awesome-awesomeness
A curated list of awesome awesomeness
datacamp_tutorials
hello-world
KOSHA-Guide
Download Design Guide from KOSHA
Probabilistic-Programming-and-Bayesian-Methods-for-Hackers
aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)
Pyinstaller-with-AHK
PyInstaller GUI version by AutoHotKey(AHK)
python-kis
📈 파이썬 한국투자증권 REST 기반 Trading API 라이브러리
Sound-Control-by-AHK
Sound Control by Autohotkey
BearCat87's Repositories
BearCat87/AHKs
My AHK library
BearCat87/awesome-AutoHotkey
A curated list of awesome AutoHotkey libraries, library distributions, scripts, tools and resources.
BearCat87/awesome-awesomeness
A curated list of awesome awesomeness
BearCat87/datacamp_tutorials
BearCat87/hello-world
BearCat87/KOSHA-Guide
Download Design Guide from KOSHA
BearCat87/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers
aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)
BearCat87/Pyinstaller-with-AHK
PyInstaller GUI version by AutoHotKey(AHK)
BearCat87/python-kis
📈 파이썬 한국투자증권 REST 기반 Trading API 라이브러리
BearCat87/Sound-Control-by-AHK
Sound Control by Autohotkey
BearCat87/Stock-Prediction-Models
Gathers machine learning and deep learning models for Stock forecasting including trading bots and simulations
BearCat87/Stock-Price-Prediction
BearCat87/stock-trading-ml
A stock trading bot that uses machine learning to make price predictions.
BearCat87/Stock_Information
NewsDB
BearCat87/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.
BearCat87/streamlit_for_me
BearCat87/ta-lib
Python wrapper for TA-Lib (http://ta-lib.org/).
BearCat87/torrequest
Simple Python interface for HTTP(s) requests over Tor