tomkess Goto Github PK

acv

package for optimal out-of-sample forecast evaluation and testing under stationarity

atp_betting

automated-fundamental-analysis

Python program that rates stocks out of 100 based on valuation, profitability, growth, and price performance metrics, relative to the company's sector.

bayesian-football

Replication of 'Bayesian hierarchical model for the prediction of football results' using pymc

book_rating

Book recommendation model.

causalnex

A Python library that helps data scientists to infer causation rather than observing correlation.

covid19_dataset_cz

covid19_dataset_cz

deep-portfolio-management

Source code for the blog post on the evolution of the asset allocation methods

deep-reinforcement-learning-for-automated-stock-trading-strategy

Stock trading strategies play a critical role in investment. However, it is challenging to design a profitable strategy in a complex and dynamic stock market. In this paper, we propose a deep ensemble reinforcement learning scheme that automatically learns a stock trading strategy by maximizing investment return. We train a deep reinforcement learn

digital-datascience-webapp

drmax-group-replenishment

duino-coin

ᕲ Duino-Coin is a coin that can be mined with almost everything, including Arduino boards.

fasttreeshap

Fast SHAP value computation for interpreting tree-based models

finqboost

Financial Portfolio Quintile Probability Forecaster #2 winner of M6 Financial Forecasting Competition

football-match-winner-prediction

Project to create machine learning models to predict the outcome of a football match

fortuna_scraper

investment-portfolio-optim

An investment portfolio of stocks was created using LSTM stock price prediction and optimized weights. The performance of this portfolio was better compared to an equally weighted portfolio and a market capitalization-weighted portfolio.

m6

mtms_sinusoidal_task

nannyml

Detecting silent model failure. NannyML estimates performance for regression and classification models using tabular data. It alerts you when and why it changed. It is the only open-source library capable of fully capturing the impact of data drift on performance.

nba-machine-learning-sports-betting

NBA sports betting using machine learning

pyprobml

Python code for "Probabilistic Machine learning" book by Kevin Murphy

qminers-hackathon

Hackathon - betting agent

qminers_hackatlon2020

stock

Stock Market Prediction Using Unsupervised Features

stock-prediction-portfolio-optimization

A Streamlit based application to predict future Stock Price and pipeline to let anyone train their own multiple Machine Learning models on multiple stocks to generate Buy/Sell signals. This is a WIP and I will keep on adding new ideas to this in future.

stock-screener-using-technical-analysis-and-portfolio-optimization-using-efficient-frontiers

The Goal of this project is to screen the individual stocks from the S&P 500 stock list and make an optimized portfolio of stocks with better returns, risk, Sharpe ratio and comparative diversity.

stockscore

A python project to fetch stock financials/statistics and perform preliminary screens to aid in the stock selection process

stockscreener

A handy tool for screening stocks based on certain criteria from several markets around the world. The list can then be delivered to your email address (one-off or regularly via crontab).

stockscreener-1

Simple S&P 500 screening with momentum and random forest algorithms.