An overview of Machine Learning Technologies and their use in E-learning

Project Code :TCMAPY381

Objective

In this paper, we are giving a brief overview of machine learning models and their use in electronic technologies. Here at first, we introduce the key concepts related to machine learning. Then, we present some recent works using machine learning in E-Learning context.

Abstract

Thanks to new technologies, internet, connected objects we produce a phenomenal amount of data. Putting these data in context, organizing them to be able to perceive, understand and reflect them is very important. Traditionally, human have analyzed data. However, as the volume of data surpasses, human increasingly turn to automated systems that can imitate him. Those systems able to learn from both data and changes in data in order to solve problems are called machine learning. Artificial intelligence has a major impact on e-learning research and the machine learning based methods can be implemented to improve Technology Enhanced Learning Environments (TELE). This paper is an overview of the recent findings in this research field. At first, we introduce the key concepts related to machine learning. Then, we present some recent works using machine learning in e-learning context.

Keywords: E-Learning, Technology Enhanced Learning Environments, Data, Learners’ Traces, Machine Learning, Deep Learning.

NOTE: Without the concern of our team, please don't submit to the college. This Abstract varies based on student requirements.

Block Diagram

Specifications

SOFTWARE SPECIFICATIONS:

  • Technology: Machine Learning, NLP.
  • Libraries: Pandas, Numpy, Scikit learn, NLTK.
  • Version: Python 3.6+
  • Server-side scripts: HTML, CSS, JS
  • Frame works: Flask
  • IDE: Pycharm

HARDWARE SPECIFICATIONS:

  • RAM: 8GB, 64-bit os.
  • Processor: I3/Intel processor
  • Hard Disk Capacity: 128 GB +

Learning Outcomes

  • Scope of Real Time Application Scenarios.
  • Objective of the project.
  • How Internet Works.
  • What is a search engine and how browser can work.
  • What type of technology versions are used.
  • Use of HTML , and CSS on UI Designs.
  • Data Parsing Front-End to Back-End.
  • Working Procedure.
  • Introduction to basic technologies used for.
  • How project works.
  • Input and Output modules.
  • Frame work use.
  • About python.
  • What is machine learning.
  • Machine learning algorithms.
  • What is electronic technologies.
  • Project Development Skills:
    • Problem analyzing skills.
    • Problem solving skills.
    • Creativity and imaginary skills.
    • Programming skills.
    • Deployment.
    • Testing skills.
    • Debugging skills.
    • Project presentation skills.
    • Thesis writing skills.

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