5 Trending Hot Research Topics in Machine Learning

1. 5 Trending Hot Research Topics in Machine Learning Machine learning is the most trending fields that have undergone incredible growth in the past few years. It is an application of artificial intelligence and is being used in different areas. There is lots of research work in this field. It is based on algorithms. The main purpose of machine learning is to create an intelligent machine that can work as human beings. There are various kinds of research topics in machine learning for mtech and phd research. But here I am going to mention only 5 most trending hot research topics in machine learning that will help you to complete your degree with well marks. Deep Learning Image Processing Data Mining Sentiment Analysis Speech Recognition

2. Deep Learning Deep Learning is a sub-field of Machine Learning. It deals with the functioning of the artificial neural network. The concept of deep learning is being used by big companies like Google, Amazon to increase their productivity and sale rate. It helps to made it possible for the practical implementation of various machine learning applications. Applications of Deep Learning Deep Learning applications will significantly affect our daily life in near future. Some of the applications have already made their impact. Here are some of the important applications of deep learning: Image Recognition Voice Assistants Self-driving cars Computer-aided medical diagnosis Automatic Machine Translation      Image Processing Image Processing is a process in which a caption or keyword is assigned to a digital image automatically. It finds its application in image retrieval systems to locate images from the database. Machine Learning methods and algorithms are applied to Automatic Image Annotation. Clustering and classification are the most commonly used methods in the process of image annotation. Data Mining To make better decisions, data mining is the process that helps to find patterns from large data- sets to extract valuable information. This technology is being used method from machine learning, statistics, and database systems for processing. There exist data mining techniques like clustering, association, decision trees, and classification for the data mining process.

3. Sentiment Analysis Sentiment Analysis is also known as opinion mining and is a process to determine whether the attitude of an individual towards a product or topic is positive, negative 0r neutral expressed in the form of text. It is another good research topic in machine learning for thesis and research. It uses the concept of natural language processing, machine learning, computational linguistics, and bioinformatics to extract essential information. It is mainly used in case of social media monitoring. Sentiment Analysis is crucial such that it helps to find what a customer thinks of a particular brand. Reinforcement Learning Reinforcement Learning is a type of machine learning algorithm in which an agent learns how to behave in an environment by interacting with that environment. A lot of research has been done in this area of machine learning in the recent times. It mostly finds its application in gaming and robotics. The approach of this algorithm is different from other machine learning algorithms which are supervised learning and unsupervised learning. The definition of reinforcement learning can be understood with the following concepts: Agent – An agent is the one that takes action in an environment. Action (A) – It is the series of steps taken by an agent in an environment. Environment – The real world in which the agent takes an action. State(S) – The situation of an agent at any particular time. Reward(R) – A type of feedback through which the success and failure of user’s actions are measured.     