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  2. Data preparation - Wikipedia

    en.wikipedia.org/wiki/Data_preparation

    Given the variety of data sources (e.g. databases, business applications) that provide data and formats that data can arrive in, data preparation can be quite involved and complex. There are many tools and technologies [5] that are used for data preparation. The cost of cleaning the data should always be balanced against the value of the ...

  3. Automated machine learning - Wikipedia

    en.wikipedia.org/wiki/Automated_machine_learning

    To make the data amenable for machine learning, an expert may have to apply appropriate data pre-processing, feature engineering, feature extraction, and feature selection methods. After these steps, practitioners must then perform algorithm selection and hyperparameter optimization to maximize the predictive performance of their model.

  4. ThoughtSpot Launches Analyst Studio, Empowering Data Teams to ...

    lite.aol.com/tech/story/0022/20250115/9332062.htm

    All in on the Analyst As AI becomes an integral driver of business processes, data teams face mounting pressure to ensure accuracy, speed up decision-making, deepen analysis, and optimize cloud costs, all across disparate solutions. Tedious and time-consuming data preparation is further stressing analysts' resources and impeding their ability ...

  5. List of datasets for machine-learning research - Wikipedia

    en.wikipedia.org/wiki/List_of_datasets_for...

    Data Management Solution to share datasets, algorithms, and experiments results through APIs. List of portals suitable for multiple types of applications [ edit ]

  6. Data transformation (computing) - Wikipedia

    en.wikipedia.org/wiki/Data_transformation...

    Data discovery is the first step in the data transformation process. Typically the data is profiled using profiling tools or sometimes using manually written profiling scripts to better understand the structure and characteristics of the data and decide how it needs to be transformed.

  7. Machine learning - Wikipedia

    en.wikipedia.org/wiki/Machine_learning

    Machine learning (ML) is a field of study in artificial intelligence concerned with the development and study of statistical algorithms that can learn from data and generalize to unseen data, and thus perform tasks without explicit instructions. [1]

  8. Data mining - Wikipedia

    en.wikipedia.org/wiki/Data_mining

    Neither the data collection, data preparation, nor result interpretation and reporting is part of the data mining step, although they do belong to the overall KDD process as additional steps. The difference between data analysis and data mining is that data analysis is used to test models and hypotheses on the dataset, e.g., analyzing the ...

  9. Instead of Dividends That Barely Pay, Look At A HYSA Instead

    www.aol.com/instead-dividends-barely-pay-look...

    Key Points from 24/7 Wall St. The average dividend yield of an S&P 500 company is less than what savings accounts are paying today.. Given that the index is up around 24% over the past year, it's ...