18Machine Learning and Deep Learning: Open Issues and Future Research Directions for the Next 10 Years

Akshara Pramod, Harsh Sankar Naicker and Amit Kumar Tyagi*

School of Computer Science and Engineering, Vellore Institute of Technology, Chennai, Tamil Nadu, India


With the development in technology, many other technologies like machine learning (ML), deep learning, blockchain technology, Internet of Things, and quantum computing have taken place in this current era. These technologies are helping human being to live their life comfortably and without any hurdle. Today, technology is helping human and protecting nature with minimum waste of available/limited resources. Among these inventions, ML and deep learning are two unique inventions which have attract many researchers or computer science researchers (or many research communities) to solve complex problems through ML. Today, ML use has been moved in many sectors to increase productivity of businesses; for example, for retail/marketing purpose, churn prediction of customers, for e-healthcare, and detecting disease in early stages. These are the few examples where ML is used in this current smart era. Together, this deep learning also has increased its importance over ML in many applications like bio-informatics, health informatics, identification of images or handwritten languages, and audio recognition. Many researchers get problematic scenario when they are not sure about particular use of machine and deep learning. ...

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