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  2. Stock market prediction - Wikipedia

    en.wikipedia.org/wiki/Stock_market_prediction

    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 information and any price changes that are not based on newly revealed information thus are inherently unpredictable. Others disagree and those with this viewpoint possess ...

  3. Predictive analytics - Wikipedia

    en.wikipedia.org/wiki/Predictive_analytics

    Predictive analytics statistical techniques include data modeling, machine learning, AI, deep learning algorithms and data mining. Often the unknown event of interest is in the future, but predictive analytics can be applied to any type of unknown whether it be in the past, present or future.

  4. Autoregressive moving-average model - Wikipedia

    en.wikipedia.org/wiki/Autoregressive_moving...

    ARMA is appropriate when a system is a function of a series of unobserved shocks (the MA or moving average part) as well as its own behavior. For example, stock prices may be shocked by fundamental information as well as exhibiting technical trending and mean-reversion effects due to market participants. [citation needed]

  5. Quantitative analysis (finance) - Wikipedia

    en.wikipedia.org/wiki/Quantitative_analysis...

    Machine learning models are now capable of identifying complex patterns in financial market data. With the aid of artificial intelligence, investors are increasingly turning to deep learning techniques to forecast and analyze trends in stock and foreign exchange markets. [15] See Applications of artificial intelligence § Trading and investment.

  6. Probabilistic programming - Wikipedia

    en.wikipedia.org/wiki/Probabilistic_programming

    Probabilistic reasoning has been used for a wide variety of tasks such as predicting stock prices, recommending movies, diagnosing computers, detecting cyber intrusions and image detection. [4] However, until recently (partially due to limited computing power), probabilistic programming was limited in scope, and most inference algorithms had to ...

  7. Online machine learning - Wikipedia

    en.wikipedia.org/wiki/Online_machine_learning

    Online learning is a common technique used in areas of machine learning where it is computationally infeasible to train over the entire dataset, requiring the need of out-of-core algorithms. It is also used in situations where it is necessary for the algorithm to dynamically adapt to new patterns in the data, or when the data itself is ...

  8. Prediction: This Will Be 2025's Top-Performing Artificial ...

    www.aol.com/prediction-2025s-top-performing...

    SOUN PS ratio, data by YCharts; PS = price to sales. However, we also know that SoundHound's current trailing-12-month revenue is set to triple by the time 2025 ends (if management's projections ...

  9. Ensemble learning - Wikipedia

    en.wikipedia.org/wiki/Ensemble_learning

    Python: scikit-learn, a package for machine learning in Python offers packages for ensemble learning including packages for bagging, voting and averaging methods. MATLAB : classification ensembles are implemented in Statistics and Machine Learning Toolbox.