Machine learning has impacted nearly every field in today’s world and the educational environment hasn't been untouched. Machine learning is the future of education and training environments. When the new brains will be trained by the teacher-machine duo, only then they’ll be able to create impactful innovations for a greater cause. This paper explores the ways Online Learning Platforms can be customized for individual students and also support teachers in creating innovative methods for imparting wisdom. These artificial learning models would help educators to make our teaching and learning environment more exciting and challenging and once implemented, would enhance the overall learning of the society. With the help of machine learning, we can fully refine the education system. This customization will consider aptitude, learning speed, background, and response of the student and even help overcome procrastination which is indeed the biggest catalyst to failure of humans in life. The educators will be able to understand and improvise the whole learning environment with the support of AI. The machine learning algorithms would perform analytics over the whole student behavior from understanding concepts, completing lessons, attempting tests, and analysis of their scores. Also to analyze their learning speed, the application would also analyze the students’, thinking and interpretation by analyzing typing and explaining speed and accuracy that would also consider voice analysis algorithms. Reducing human intervention in such analytics would help create more time for the students and well the teachers to create and implement new strategies for better results. Online education technology has a huge cost of development of resources. Deep Learning uses AI to offers customized learning. This paper aims to survey various applications of Deep Learning approaches for the development of resources for an E-Learning platform which include predictions and algorithms for building. Also, the analytics supports the overall development of the application. The deep learning model for developing the contents and the framework for development, future scope, and the important tools that use this technology are reviewed.



Software And Hardware