提供股票，基金，债券，期货，以及市场相关行业数据

Construct workable datasets from web data and applied various machine learning methods to predict future oil price

This project highlights a Spark application built on Scala. It utilizes Spark Core, Spark SQL and Spark ML (Machine Learning libraries) for predicting stock prices of specific airline companies. We have used the Google trending words (searched on internet and relevant to financial domain) and also macro-economic oil prices as alternate data to p…

The goal of our analysis was to use different time series methods to predict the oil price for the last 6 months of the data, September 2017 through February 2018, and determine the best prediction model for this data.

A Python code for a Personal Assistant which performs various tasks. Search google,Wikipedia, and gives stock prices with Oil prices .

Repository untuk mengerjakan project tugas akhir prodi Teknik Informatika UBHARA Surabaya

Problem to solve: Determine what role oil plays in the Russia economy and predict outcomes in the years to come. Data: year (From 2004 to 2018), oilprice (The spot price of a barrel (159 liters) of benchmark crude oil in US dollars, gpd (Gross domestic product in billions of US dollars

extract oil and gas prices data based on oilprice-api into CSV file

Projects relevant to the oil & gas industry built by Microsoft

Node.js based API for getting oil and gas prices based on oilprice.com

Predicting Crude Oil prices for the next 5 days using ARIMA model

Key Factors Affecting Oil Prices and the Market Share of ICE, HEV, and EV in Malaysia

A project which aimed to see just how much does the price of crude oil influences the retail price of gas

Real-time commodity price alerts in Salesforce. Open-source Apex webhook integration with HMAC security. Production-tested.

Official Python SDK for OilPriceAPI - Real-time and historical oil, gas, and energy commodity price data

Daily Brent Crude oil prices from 1987 to the present, obtained from the EIA (US Energy Info. Administ.) via FRED, were used as the dataset. The last two years were used as test data, and the performance of forecasting models was measured. XGBoosting yielded the best results. The article link containing storytelling about this repository is below.

Parse Oil Price Data Written in NodeJS

获取最新的油价信息，数据源http://www.qiyoujiage.com/zhejiang.shtml

A linear model on NYMEX WTI Crude Oil weekly data that predicts the High and Low of each based on the Open, Close, and Volume.