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alteryx_filters

Python Script to extract filters and formulas used in alteryx workflows.

auto-gpt-metatrader-plugin

The AutoGPT MetaTrader Plugin is a software tool that enables traders to connect their MetaTrader 4 or 5 trading account to Auto-GPT.

auto-gpt-plugin-template

A starting point for developing your own plug-in for Auto-GPT

data

Data and code behind the articles and graphics at FiveThirtyEight

dynamic-prices

Dynamic pricing for selling perishable goods

dynamic-pricing-algorithms

A model algorithm to provide practical insights into pricing mechanisms

dynamic_pricing

This machine learning model (deep and wide learning model) helps us to implement dynamic pricing feature of a supply chain business problem. This model uses tensorflow to solve the probelm and help create a model.

hello-world

hrockhill3.github.io

Professional Portfolio and Blog using mmistakes framework

jekyll-twitter-plugin

A Liquid tag plugin for the Jekyll blogging engine that embeds Tweets, Timelines and more from Twitter API

langchain-tutorials

Overview and tutorial of the LangChain Library

lstm-dynamic-pricing-model

machine_learning_def

defining Machine Learning

optimal-price-based-control-of-heterogeneous-thermostatically-controlled-loads-under-uncertainty-usi

we consider the problem of thermostatically controlled load (TCL) control through dynamic electricity prices, under partial observability of the environment and uncertainty of the control response. The problem is formulated as a Markov decision process where an agent must find a near-optimal pricing scheme using partial observations of the state and action. We propose a long-short-term memory (LSTM) network to learn the individual behaviors of TCL units. We use the aggregated information to predict the response of the TCL cluster to a pricing policy. We use this prediction model in a genetic algorithm to find the best prices in terms of profit maximization in an energy arbitrage operation. The simulation results show that the proposed method offers a profit equal to 96% of the theoretical optimal solution.

priceoptimization

Leveraging the dynamic pricing strategy by using supervised machine learning algorithm to predict the optimal price for a certain product/service

pycon_sg_2016

PyCon SG 2016 - Customer Segmentation in Python

pyfin

Basic options pricing in Python

revpy

Collection of some revenue management tools for python 3

sagemaker-101-xgboost

Build, train, and deploy a bank enrollment predictor with Amazon SageMaker and XGBoost

sagemaker-rec-demo

Recommendation engine example notebook using Amazon SageMaker and Factorization Machines

seat-optimizer

For the purpose of building out the optimal number of seats based on conditions to experiment with capacity and distribution

stochasticdynamicpricing

I will use a stochastic model assuming that my customers follow Poisson law and then use Lagrangian Method to find the optimum price for users based on the number of sales

tweepy_scrape

scrape tweets and sentiment based on date, screen name, and hashtags

woocommerce-dynamic-pricing

WooCommerce Dynamic Pricing, Git-ified. Synced manual! This repository is just a mirror of the WooCommerce Dynamic Pricing plugin. Please do not send pull requests.