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nempy

A flexible tool kit for modelling Australia's National Electricity Market dispatch procedure.

netloadforecasting

neural-finance

【State of the art】Using deep learning in quantitative finance

neural_prophet

NeuralProphet - A simple forecasting model based on Neural Networks in PyTorch

ngboost

Natural Gradient Boosting for Probabilistic Prediction

ngboost-experiments

Play around with NGBoost and compare with LightGBM and XGBoost

nn-svg

Publication-ready NN-architecture schematics.

office_automation_by_using_python

Office Automation by Using Pythonf (For Excel, Word, PPT and PDF .....)

open_source_demos

A collection of demos showcasing automated feature engineering and machine learning in diverse use cases

openmodelica-microgrid-gym

OpenModelica Microgrid Gym (OMG): An OpenAI Gym Environment for Microgrids

optiongan

Code accompanying the OptionGAN paper.

optuna

A hyperparameter optimization framework

opyrator

🪄 Turns your machine learning code into microservices with web API, interactive GUI, and more.

pairs-trading-with-machine-learning

Pair Trading Strategy using Machine Learning written in Python

pairs-trading-with-ml

panama-electricity-load-forecast

Regression model to forecast pre-dispatch electricity demand based on historical national demand.

pandapy

PandaPy has the speed of NumPy and the usability of Pandas 10x to 50x faster (by @firmai)

paper-implementation-dstp-rnn-for-stock-prediction-based-on-da-rnn

基於DA-RNN之DSTP-RNN論文試做(Ver1.0)

papermill

📚 Parameterize, execute, and analyze notebooks

papers

Code and data for my papers

pcedl

Wind Turbine Power Curve Estimation using Deep Learning methods

peaky-finders

ISO peak load forecasting application

phd-windpoweroutput

Simple Wind Turbine Design and Wind Power output calculations using Weibull and Power curve

plexos-analysis-scripts

A collection of scripts that are specific useful implementations of PLEXOS API

power_curve_estimation

Wind energy is one of the fastest growing renewable energy sources. According to a report issued by the U.S. Department of Energy (DOE), wind power installation in the United States increased by nearly a factor of 10 in the past decade, from 6350 megawatts (MW) in 2003 to 61,108 MW by the end of 2013 (DOE 2014). The DOE advocates working toward the goal that wind power accounts for 20% of the total electricity generated in the United States by 2030 (DOE 2008).

predicting-daily-stock-returns-with-machine-learning-models

My first Machine Learning project

prereise

Prepare time series of renewable generators

presentations

Slide show presentations regarding data driven investing.

probabilistic-load-forecasting-with-quantile-regression

Comparison study of GB, XGB, LGBM and NN's performance in probabilistic load forecasting

probabilistic-sharpe-ratio

Probabilistic Sharpe Ratio example in Python (by Marcos López de Prado)