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  2. Long short-term memory - Wikipedia

    en.wikipedia.org/wiki/Long_short-term_memory

    In theory, classic RNNs can keep track of arbitrary long-term dependencies in the input sequences. The problem with classic RNNs is computational (or practical) in nature: when training a classic RNN using back-propagation, the long-term gradients which are back-propagated can "vanish", meaning they can tend to zero due to very small numbers creeping into the computations, causing the model to ...

  3. Stock market prediction - Wikipedia

    en.wikipedia.org/wiki/Stock_market_prediction

    Intrinsic value (true value) is the perceived or calculated value of a company, including tangible and intangible factors, using fundamental analysis. It's also frequently called fundamental value. It is used for comparison with the company's market value and finding out whether the company is undervalued on the stock market or not.

  4. Recursive neural network - Wikipedia

    en.wikipedia.org/wiki/Recursive_neural_network

    A recursive neural network is a kind of deep neural network created by applying the same set of weights recursively over a structured input, to produce a structured prediction over variable-size input structures, or a scalar prediction on it, by traversing a given structure in topological order.

  5. Predictive analytics - Wikipedia

    en.wikipedia.org/wiki/Predictive_analytics

    Predictive analytics is a set of business intelligence (BI) technologies that uncovers relationships and patterns within large volumes of data that can be used to predict behavior and events. Unlike other BI technologies, predictive analytics is forward-looking, using past events to anticipate the future. [3]

  6. Bootstrap aggregating - Wikipedia

    en.wikipedia.org/wiki/Bootstrap_aggregating

    This makes random forests particularly useful in such fields as banking, healthcare, the stock market, and e-commerce where it is important to be able to predict future results based on past data. [7] One of their applications would be as a useful tool for predicting cancer based on genetic factors, as seen in the above example.

  7. Prediction - Wikipedia

    en.wikipedia.org/wiki/Prediction

    Prediction market. Mathematical models of stock market behaviour (and economic behaviour in general) are also unreliable in predicting future behaviour. Among other reasons, this is because economic events may span several years, and the world is changing over a similar time frame, thus invalidating the relevance of past observations to the ...

  8. Airbnb stock surges as CEO aims to make app the 'Amazon ... - AOL

    www.aol.com/finance/airbnb-stock-surges-ceo-aims...

    Airbnb stock surged more than 14% in early trading Friday following an earnings beat as CEO Brian Chesky said he wanted to make the vacation home marketplace app more than a destination for people ...

  9. Nonlinear autoregressive exogenous model - Wikipedia

    en.wikipedia.org/wiki/Nonlinear_autoregressive...

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