Forecasting emerging technologies using data augmentation and deep learning

Improving Deep Learning using Generic Data Augmentation

Deep artificial neural networks require a large corpus of training data in order to effectively learn, where collection of such training data is often expensive and laborious. Data augmentation overcomes this issue by artificially inflating the training set with label preserving transformations. Recently there has been extensive use of generic data augmentation to improve Convolutional Neural N...

Machine Learning Models for Housing Prices Forecasting using Registration Data

This article has been compiled to identify the best model of housing price forecasting using machine learning methods with maximum accuracy and minimum error. Five important machine learning algorithms are used to predict housing prices, including Nearest Neighbor Regression Algorithm (KNNR), Support Vector Regression Algorithm (SVR), Random Forest Regression Algorithm (RFR), Extreme Gradient B...

Emerging technologies for learning

Emerging E-Learning Technologies

E-learning offers a tremendous amount of new features, including time and location independent studying, consolidation of a bundle of learning resources over the Internet, and presentation of e-learning content in various media types. These benefits significantly improve the effectiveness of learning for e-learning users. Hence, many institutions or organizations have already adopted or had a t...

Improving Stock Return Forecasting by Deep Learning Algorithm

Improving return forecasting is very important for both investors and researchers in financial markets. In this study we try to aim this object by two new methods. First, instead of using traditional variable, gold prices have been used as predictor and compare the results with Goyal's variables. Second, unlike previous researches new machine learning algorithm called Deep learning (DP) has bee...