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abydos

Abydos NLP/IR library for Python

alpha_vantage

A python wrapper for Alpha Vantage API for financial data.

analytics_vidhya

Codes related to activities on AV including articles, hackathons and discussions.

backtesting.py

:mag_right: :chart_with_upwards_trend: :snake: :moneybag: Backtest trading strategies in Python.

backtrader

Python Backtesting library for trading strategies

chart-doctor

Sample files to accompany the FT's Chart Doctor column

echostatenetworks

Materials related to the Medium article "Predicting Stock Prices with Echo State Networks".

endtoend---predictive-modeling-using-python

fastquant

fastquant — Backtest and optimize your trading strategies with only 3 lines of code!

featexp

Feature exploration for supervised learning

functime

Time-series machine learning at scale. Built with Polars for embarrassingly parallel feature extraction and forecasts on panel data.

homemade-machine-learning

🤖 Python examples of popular machine learning algorithms with interactive Jupyter demos and math being explained

pandas-usaddress

The usaddress library made easy with Pandas

population-stability-index

Python implementation of the population stability index (PSI)

practicalai

📚A practical approach to learning machine learning.

psi

Population stability index

pygwalker

PyGWalker: Turn your pandas dataframe into an interactive UI for visual analysis

python-100-days

Python - 100天从新手到大师

scorecardpy

Scorecard Development in python, 评分卡

shap

A unified approach to explain the output of any machine learning model.

stock-prediction-models

Gathers machine learning and deep learning models for Stock forecasting, included trading bots and simulations

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.

stockstats

Supply a wrapper ``StockDataFrame`` based on the ``pandas.DataFrame`` with inline stock statistics/indicators support.

usaddress-scourgify

Clean US addresses following USPS pub 28 and RESO guidelines

variable-selection-using-python

woe-and-iv