The Study of Machine Learning to Deep Learning along with Applications

Abstract

Over the past few decades, Artificial Intelligence and machine learning techniques have been generally adopted in numerous fields such as medicine, biology and recommender systems and so on. In any case, as the time for big data is coming, collection of large data sets and processing these datasets with the conventional machine learning algorithms becomes a complex task and in some cases the results are inaccurate. Many of these techniques are designed in such a way that, the data would be loaded into the memory, but it may not possible in the context of analyzing the big data. On the other hand, deep learning refers to machine learning techniques that utilize either supervised or unsupervised techniques to learn the hierarchical features automatically using neural networks comprised of several layers. It has pulled much attention in recent years because of its best performance in areas like speech recognition, computer vision, and natural language processing, etc. As the data becomes bigger in the applications, deep learning comes into the picture and played a prominent role in several predictive applications. In this paper we presented an overview of machine learning and the problem of it while handling the big data. Further, we presented the deep learning along with the key applications i.e. speech recognition, computer vision and recommender systems followed by describing the popular deep learning models.