Stock market price prediction is difficult and complex task. Prediction in stock very unstable Process. Price are most of the time tend to follow patterns those more or less regular curve. Machine Learning techniques use different predictive models algorithms predict automate things reduce human effort. This research paper focuses on Long Short Term Memory (LSTM) future company using each day c...

Video prediction has been an active topic of research in the past few years. Many algorithms focus on pixel-level predictions, which generates results that blur and disintegrate within a few frames. In this project, we use a hierarchical approach for long-term video prediction. We aim at estimating high-level structure in the input frame first, then predict how that structure grows in the futur...

This paper presents a method to predict retrieval terms from relevant/surrounding words or descriptive texts in Japanese by using deep belief networks (DBN), one of two typical types of deep learning. To determine the effectiveness of using DBN for this task, we tested it along with baseline methods using examplebased approaches and conventional machine learning methods, i.e., multi-layer perce...

Long-term memory prediction extends motion compensation from the previously decoded frame to several past frames with the result of increased coding ee-ciency. In this paper we demonstrate that combining long-term memory prediction with aane motion compensation leads to even higher coding gains. For that, various aane motion parameter sets are estimated between frames in the long-term memory bu...

BACKGROUND Targeted interventions for the long-term sick-listed may prevent permanent exclusion from the labour force. We aimed to develop a prediction method for identifying high risk groups for continued or recurrent long-term sickness absence, unemployment, or disability among persons on long-term sick leave. METHODS We obtained individual characteristics and follow-up data from the Danish...