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artificial-neural-network-churn-model

ANN for predicting whether a bank customer will stay or leave

bank_churn_ml_dashboard

chembl-compounds-scraper

cnn-image-recognition

A Combination CNN model using InceptionV3 via transfer learning for image classification

da-rnn

Dual-Stage Attention-Based Recurrent Neural Network for financial time-series prediction

fastgoertzel

A fast implementation of the goertzel algorithm made in Rust.

fractional-differencing-sarima

Comparing SARIMA models with First Order vs Fractional Differencing

hellinger-distance-criterion

Random Forest model using Hellinger Distance as split criterion

hht-mars

A hybrid forecasting model that combines the Hilbert-Huang Transform and Multivariate Adaptive Regression Splines

ixis-data-science-challenge

mars-regression-stock-forecast

Forecasting the next day stock price for a given asset utilizing the multivariate adaptive regression splines algorithm and web scraping to get the VIX percent change

mars-time-series

Multivariate Adaptive Regression Splines for Time Series Prediction

mesa-forecast

modwt-mars

Evaluation of Hybrid MODWT-MARS framework for financial time series forecasting

one-rep-max-calculator

A simple python program to calculate your one rep max estimate using PyQt5 to make the application

poem-generator

A GPT2 instantiation trained on poems for text generation

python-rcs

Recoil Control System for CS:GO in Python

recurrent-neural-network

a RNN trained on daily Apple Stock price

shap

Fork of Shap with updates to work better on Windows

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.

streamlit-automl

taco-bell-menu-optimization

A Streamlit app that uses web scrapping and linear optimization to create Taco Bell order combos based on a user's nutritional constraints

thinkscript-strategies

Collection of Thinkscript strategies I've built

vwap-mean-reversion

A VWAP based mean reversion trading strategy

wavelet-boundary-effect-reduction

A method for eliminating boundary effects from wavelet denoising to be used as a possible filter in trading

wavelet-coherence

Research Paper that looks into correlation and co-movement between Oil (CL) and the S&P500 (ES) markets by employing wavelet coherence analysis on both price and volatility