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Long short-term memory ( LSTM) [1] is a type of recurrent neural network (RNN) aimed at dealing with the vanishing gradient problem [2] present in traditional RNNs. Its relative insensitivity to gap length is its advantage over other RNNs, hidden Markov models and other sequence learning methods. It aims to provide a short-term memory for RNN ...
Stock market prediction. Stock market prediction is the act of trying to determine the future value of a company stock or other financial instrument traded on an exchange. The successful prediction of a stock's future price could yield significant profit. The efficient market hypothesis suggests that stock prices reflect all currently available ...
Machine learningand data mining. These datasets are used in machine learning (ML) research and have been cited in peer-reviewed academic journals. Datasets are an integral part of the field of machine learning. Major advances in this field can result from advances in learning algorithms (such as deep learning ), computer hardware, and, less ...
Meanwhile, travel for players and fans, in addition to stadium power use, contributes to high emissions by the NFL, MLS, NBA, NHL and MLB. Which is why SailGP, a sport powered by the wind, tries ...
In other words, civics is a 21st-century business skill. Critical thinking, problem-solving, negotiation, curiosity, adaptability, shared risk-taking, and other so-called “soft skills” are ...
Fama–MacBeth regression. The Fama–MacBeth regression is a method used to estimate parameters for asset pricing models such as the capital asset pricing model (CAPM). The method estimates the betas and risk premia for any risk factors that are expected to determine asset prices.
A new study shows that crows, in this case the carrion crow, can count out loud just like human toddlers. This discovery opens up new doors for more complex conversation among crows, who are also ...
The Hilbert–Huang transform ( HHT) is a way to decompose a signal into so-called intrinsic mode functions (IMF) along with a trend, and obtain instantaneous frequency data. It is designed to work well for data that is nonstationary and nonlinear. In contrast to other common transforms like the Fourier transform, the HHT is an algorithm that ...