Popular GitHub Repositories for Pricing

Metering and Billing for AI, API and DevOps. Collect and aggregate millions of usage events in real-time and enable usage-based billing.

A collection of reference Jupyter notebooks and demo AI/ML applications for enterprise use cases: marketing, pricing, supply chain, smart manufacturing, and more.

Backtest 1000s of minute-by-minute trading algorithms for training AI with automated pricing data from: IEX, Tradier and FinViz. Datasets and trading performance automatically published to S3 for building AI training datasets for teaching DNNs how to trade. Runs on Kubernetes and docker-compose. >150 million trading history rows generated from +5000 algorithms. Heads up: Yahoo's Finance API was disabled on 2019-01-03 https://developer.yahoo.com/yql/

Chargym simulates the operation of an electric vehicle charging station (EVCS) considering random EV arrivals and departures within a day. This is a generalised environment for charging/discharging EVs under various disturbances (weather conditions, pricing models, stochastic arrival-departure EV times and stochastic Battery State of Charge (BOC) at arrival). This is an open source OpenAI Gym environment for the implementation of Reinforcement Learning (RL), Rule-based approaches (RB) and Intelligent Control (IC).

Discrete choice modeling in Python with large datasets & models - Assortment & Pricing Optimization .

A demo application that uses Amazon SageMaker manuals and pricing data tables as an example to explore the capabilities of a generative AI chatbot.

Optimising electricity expenditure in an HVAC system under dynamic electricity pricing scheme and weather conditions using a DDPG model.

Parse SaaS pricing page using Open AI - GPT-3.5

A DQN agent that optimally hedges an options portfolio.

Scientific Machine Learning for Option Pricing

DeepTrust: A Reliable Financial Knowledge Retrieval Framework For Explaining Extreme Pricing Anomalies

Custom Neuron Decision-Making and Visual Workflow Orchestration Quantitative

Pricing Financial Options contracts using LightGBM, Deep Learning, and Support Vector Machines.

DeepAir Solutions : Price recommendations for ancillary facilities for airline using deep reinforcement learning. AAP refers to Airline Ancillary Pricing.

In this project, I explore various machine learning techniques including Principal Component Analysis (PCA), Support Vector Machines (SVM), Artificial Neural Networks (ANN), and Sentiment Analysis in an effort to predict the directional changes in exchange rates for a list of developed and developing countries.

Consignment pricing prediction using mlops

A simple, interactive web tool to compare pricing and performance metrics of various AI models.

GLM, Neural Network and Gradient Boosting for Insurance Pricing, Part 1: Claim Frequency

Explore pricing data. Share insights and models. Build environment for repricer.

Implied volatility is a key aspect when it comes to derivatives pricing. With the growing influence of machine learning in finance, I have investigated the use of LSTMs to forecast 1-day forward Implied Volatility.