ANALYSIS OF INTELLIGENT TECHNIQUES INPERSONALIZATION IN E-LEARNING SYSTEMS

An eLearning approach is nearly ready, in which the learning community has the right digital infrastructure, mobile phones, tablets and the best software platform. Innovation has become an integral part of the educational and learning fields and is obligatory. The goal is therefore to provide students with standard and appropriate instructional materials. The research aims to classify the learner according to their learning skills and to find a path to enable the learner, by using machine-learning methods, to have suitable and quality learning objects. The goal is to build and adapt the learner style to a system architecture that will find the learning path and provide appropriate learning artifacts according to your preferences. E-Learning environment. This paper offers an overview of smart methods which can be used for personalization in various phases of e-learning systems. It provides examples of its application to various e-learning platforms for building learner profiles and identifying learning routes. The use of online learning systems that continuously develop takes a key role in adapting to oneself, particularly for working people. In reality, learning systems most of the time do not conform to the profiles of learners. Learners must spend a lot of time before hitting the learning target that is ideal for their experience. This paper explores machine learning in e-learning systems and its implementations. Machine learning is a kind of artificial intelligence (AI) that allows machines to learn without being customised explicitly.