Neural networks, recognizing patterns

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HL content: Modeling & Simulation[1]

Introduction

Examples include:

Speech recognition

Speech recognition is the inter-disciplinary sub-field of computational linguistics that develops methodologies and technologies that enables the recognition and translation of spoken language into text by computers.[2]

  1. One of the very best articles I have ever seen on speech recognition and neural networks.
  2. Click here for a REALLY bad video trying to describe this.
  3. Click here for a more advanced video on this

Neural network speech.png

Optical character recognition

Optical character recognition...is the mechanical or electronic conversion of images of typed, handwritten or printed text into machine-encoded text.[3].

Please note: none of the resources I could find are excellent. But taken together as a whole, they should help improve your understanding of how neural networksa group or system of interconnected people or things. work with OCR.

Natural language processing

Natural language processing (NLP) is a subfield of computer science, information engineering, and artificial intelligence concerned with the interactions between computers and human (natural) languages, in particular how to program computers to process and analyzeBreak down in order to bring out the essential elements or structure. To identify parts and relationships, and to interpret information to reach conclusions. large amounts of natural language data.[4].

Standards

  • Compare applications that use neural networka group or system of interconnected people or things. modelling.
  • Compare different ways in which neural networksa group or system of interconnected people or things. can be used to recognize patterns.

References