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  2. Computational Spectroscopy In Natural Sciences and ...

    en.wikipedia.org/wiki/Computational_Spectroscopy...

    The main purpose of COSINE is the development of ab-initio research tools to study optical properties and excited electronic states, which are dominated by electron correlation. This tools are developed for the investigation of organic photochemistry with the aim of accurate simulation of spectroscopic experiments on the computer.

  3. Data-driven learning - Wikipedia

    en.wikipedia.org/wiki/Data-driven_learning

    Data-driven learning (DDL) is an approach to foreign language learning. Whereas most language learning is guided by teachers and textbooks, data-driven learning treats language as data and students as researchers undertaking guided discovery tasks. Underpinning this pedagogical approach is the data - information - knowledge paradigm (see DIKW ...

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

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

    High-quality labeled training datasets for supervised and semi-supervised machine learning algorithms are usually difficult and expensive to produce because of the large amount of time needed to label the data. Although they do not need to be labeled, high-quality datasets for unsupervised learning can also be difficult and costly to produce ...

  5. Data modeling - Wikipedia

    en.wikipedia.org/wiki/Data_modeling

    The database design documented in these schemas is converted through a Data Definition Language, which can then be used to generate a database. A fully attributed data model contains detailed attributes (descriptions) for every entity within it. The term "database design" can describe many different parts of the design of an overall database ...

  6. Data-driven model - Wikipedia

    en.wikipedia.org/wiki/Data-driven_model

    Data-driven models encompass a wide range of techniques and methodologies that aim to intelligently process and analyse large datasets. Examples include fuzzy logic, fuzzy and rough sets for handling uncertainty, [3] neural networks for approximating functions, [4] global optimization and evolutionary computing, [5] statistical learning theory, [6] and Bayesian methods. [7]

  7. Instructional design - Wikipedia

    en.wikipedia.org/wiki/Instructional_design

    Instructional design (ID), also known as instructional systems design and originally known as instructional systems development (ISD), is the practice of systematically designing, developing and delivering instructional materials and experiences, both digital and physical, in a consistent and reliable fashion toward an efficient, effective, appealing, engaging and inspiring acquisition of ...

  8. Database theory - Wikipedia

    en.wikipedia.org/wiki/Database_theory

    Database theory encapsulates a broad range of topics related to the study and research of the theoretical realm of databases and database management systems.. Theoretical aspects of data management include, among other areas, the foundations of query languages, computational complexity and expressive power of queries, finite model theory, database design theory, dependency theory, foundations ...

  9. Learning object metadata - Wikipedia

    en.wikipedia.org/wiki/Learning_object_metadata

    Learning Object Metadata is a data model, usually encoded in XML, used to describe a learning object and similar digital resources used to support learning. The purpose of learning object metadata is to support the reusability of learning objects, to aid discoverability , and to facilitate their interoperability, usually in the context of ...