Interesting Research Topics in Machine learning you must know

Interesting Research Topics in Machine learning you must know Presently, machine learning is seen as the most popular field of study in the research topic and students prefer opting for the same subject area to write their research paper. Machine learning is a vast concept and the amount of information that is available for the students is more than enough. However, under such a vast concept, how one can find a topic that will be the best and relevant for the research paper.

To help you get your hands on handful of the interesting research topics in the respective field, check out following list: Supervised Learning As the name suggests, supervised learning refers to learning tasks under some sort of supervision, for example, a teacher supervises his student in how he can write his research paper excellently. The datasets are labeled in supervised learning so that algorithms or models can use them to identify, analyze, and classify data along with foreseeing the results accurately.

Unsupervised Learning Unlike supervised learning, unsupervised learning takes the help of artificial intelligence to come up with accurate results after identifying dataset patterns without any labels. To make it sound simpler, unsupervised learning gives the algorithms or systems to learn about different patterns given in a dataset on their own.

Neural Network A neural network consists of neurons – organic or artificial that allows the system to identify relationships in a single dataset in the way the human brain functions. In other words, neural networks act and function like a human brain to allow computer systems to identify various patterns & relationships between them able to solve artificial intelligence, machine learning, and deep learning problems.

Back-Propagation In machine learning, backpropagation is a method through which specific fields of the neural network are trained.

Meaning thereby, it is a principle that helps machine learning to alter its present functioning without looking at how it used to function in the past. At times, backpropagation is known as ‘backpropagation of errors’.

Logistic Regression Logistic regression is known to be a subpart of a supervised machine learning system with the help of which, problems found in the pattern of dataset or whole dataset are classified easily. Logistic regression is found to be of two types namely – binary and multi-class. The best examples of the classifying problems are as follows –  

Email spam or no email spam.

Fraud online transaction or not fraud online transaction.

K-Nearest Neighbors It is abbreviated as K-NN and is the most simple and easy to implement. Both the problems – classification and regression, can be easily solved with the help of K-NN. It is based on the fact that the more things are simple, more nearer they will be. K-NN can also be used in recommendation systems.

Other interesting yet important research topics in machine learning are –           

Linear learning Random forest Ensemble learning Overfitting Underfitting Deep learning Artificial intelligence Regularization L1 and L2 regularization Cross-validation Performance metrics for regression