MIT Technology Review

Using unstructured data to fuel enterprise AI success

Organizations have a wealth of unstructured data that most AI models can’t yet read. Preparing and contextualizing this data is essential for moving from AI experiments to measurable results.

AI Models Are Starting to Learn by Asking Themselves Questions

An AI model that learns without human input—by posing interesting queries for itself—might point the way to superintelligence ...
IEEE

Profit Prediction Using ARIMA, SARIMA and LSTM Models in Time Series Forecasting: A Comparison

Abstract: Time series forecasting using historical data is significantly important nowadays. Many fields such as finance, industries, healthcare, and meteorology use it. Profit analysis using ...
IEEE

Forecasting Ability of Hybrid Methods on an Example of Stock Prices Forecast using ARIMA/LTSM

Abstract: The paper presents the research results of the predictive ability of stock quote forecasting models using the ARIMA/LSTM hybrid model. This study is based on a predictive power analysis ...