Natural language processing using deep learning

This paper proposes an efficient and novel technique for assessment of the direction of switched capacitor bank as well as estimating its distance from the monitoring location in real distribution systems. At first, the proposed …. Models and methods of natural language processing are studied to create an algorithm capable of accurately determining the belonging of a literary work to a certain group based on common characteristics and elements. Existing methods of natural language processing used in text classification problems are assessed. A sequence of effective actions - an algorithm - for determining book genres on "home" computer equipment is designed and developed. An important component of the resulting algorithms and models is the ability to select available computing resources. In the modern world, the exponential growth of text data has become a serious problem for organizations and companies. With the digitization of everything - emails to documents and e-mail - the volume of text data that must be managed, stored and structured is constantly increasing. Partially, this problem can be solved using machine natural language processing. As the volume of this information continues to grow, an urgent problem has arisen of automating routine human tasks associated with the classification and structuring of this huge amount of information. Solving this problem is crucial to ensuring the effective management of ever-growing volumes of data. With the growing importance of natural language processing in today's datadriven economy, it is critical to gain insight into its capabilities and limitations, which is one of the objectives of this paper.