What are Good Topics in Machine Learning for Master Thesis in Computer Science

Today the interest in machine learning is so great that it is the most active research area in artificial intelligence. If we define Machine Learning (ML), then ML is a field of study that gives computers the ability to learn without being explicitly programmed. Machine Learning for Master Thesis interest is increasing rapidly.

Trends are changing with the passage of time before Software Engineering and Networks were considered for the thesis purposes. Now ML has given new hope and new ideas. Mouse to laptop everything is becoming smart and even more intelligent.

Therefore, it is challenging for some students to start working in ML if they don’t know its sub-topics. There are many topics and areas in which researchers are doing work. We are going to show you some of the most recent research topics in ML with some little introduction to complete your master’s thesis.

Below is list of some hot topics in ML

  • Machine learning algorithms
  • Pattern recognition machine learning
  • Supervised machine learning
  • ML classification
  • UCI machine learning
  • Machine learning intrusion
  • Machine learning repository
  • Gaussian processes
  • Malware
  • Unsupervised machine learning
  • Data mining
  • Ensemble
  • Genetic algorithms
  • Intrusion detection
  • Anomaly detection
  • Random Forests
  • Sentimental Analysis
  • Social Network Graphs
  • Recommender Systems
  • Neural Networks
  • Information Retrieval

When you type all these keywords in Google Scholars or IEEE library, you will find further subtopics that is why ML is becoming the choice of every single identity in current organization trends. You type some keywords in Google Scholar such as  “survey” and “review” with other keywords for the domain like “energy”, “security”, “cancer”, and then also some terms like: “big data”, “feature selection”, “Naive Bayes”, etc. We have listed some of the current research fields, but there exist many others such as:

  • Database mining
  • Large dataset from growth of automation and web application
  • Medical records monitoring for early safety to handle certain diseases attacks
  • Autonomous Helicopters
  • Hand Writing recognition
  • Natural Language Processing
  • Probalistic modelling of data
  • Gene Sequencing
  • Speech recognition
  • Image annotation
  • Reinforcement learning
  • Adversarial training
  • Human brain decoding (Multi-Voxel Pattern Analysis)

See also: How to write PhD proposal in Computer Science

When I started to research, then my supervisor told me to read at least 3 to 4 survey papers, survey papers regarding ML have many approaches and algorithms that give you initial intuition on how to do the black boxing of Machine Learning. There are many algorithms exist which are mostly used in data sciences to collect useful information from the text. These are:

  1. Supervised Learning
  2. Un-Supervised Learning

In supervised learning output is given, it is divided into further two types, Regression for Continuous values prediction such as house price predictions and Classification which is used for discrete classification such as email is spam or not.

Explaining algorithm is not our concern. Topic of discussion is to provide MS students a reasearch idea for their thesis in the field of computer science, mathematics and stats.

Machine Learning Thesis Topics:

On the top list, the hot topic is Sentimental Analysis. Issues in this field include:

  1. Prediction of election results by users tweets posted on twitter
  2. Prediction of freelancing projects, either it will be awarded to any freelancer or not? From the description he provided
  3. Prediction of price of Laptop or any other electronics, or any thing which is used in daily life from the features available in it
  4. Prediction of Spam website links
  5. Early detection of diseases spread, from the symptoms shared on social networks by a different user. This type of work will be completed using geographical location of that user, who has shared his/her symptoms
  6. Controversial news detection
  7. Automatic diagnosis of disease called the intelligent disease diagnosis (IDD) expert system
  8. Personality prediction by friend’s circle of a user on social networks
  9. Sequential Pattern mining from text to detect most used controversial, hate promoting words from social networks
  10. Sentimental Analysis to improve the quality of products using surveys, reviews and comments
  11. Selection of Airlines, Hotels from previous users feedback
  12. Career Counseling of students from their previous records in academics
  13. Proposing a series of actions to achieve a goal
  14. Develop a model, which predicts agricultural growth from rainfall, plant growth
  15. You can design a web application, which starts recommending you next pages, on the basis of user previous searching
  16. User behavior on websites to place advertisement on a specific area of web page
  17. Image segmentation of biologically useful images, for example if you are going for a walk in a park, and you take pictures of same plant at different location, then is there any way to predict the number of branches a plant have, its age, pest prevalence etc.

Machine Learning Hot Topics for Research in MS:

These are some topics, but please pick a small problem and find results using different machine learning problems, then try to optimize results to increase efficiency.As a result  you find good topic to start research. There are some other root topics such as:

  1. Graphical Models
  2. PCA
  3. Neural Networks
  4. Bayesian Networks
  5. Support Vector Machine (SVM)
  6. Kernels
  7. Classification techniques

In recent years the research in neural networks has been very intensive and remarkably good results have been achieved. This is particularly the case in connection with speech and image recognition. For example, you are given a sample of image; now you have to design a neural network which decides what actually image represents from the below choices

  1. Pedestrian
  2. Car
  3. Motorcycle
  4. Truck

This is still a classification task, but this time your hypothesis will efficiently classify non-linear results. In other words, you need to design a system that can identify one or more objects from the features present in it.

You can also redirect your research using neural networks such as to detect a person either he is happy or not from his facial expressions. There is another tip to find either person is lying or not this may be a good idea for MS thesis.

There is vast space in this field. From MS thesis point of view, then novelty isn’t needed at this stage. Try to pick those topics which you can easily manage to complete your thesis in a defined timeframe.

Tools Used in Machine Learning:

There are different ways to find results from your data such as the most widely used is WEKA, KEEL and Matlab. Some researchers implement their problems in Python, Octave and some use R. Python mostly used to modify the existing algorithms available to improve the efficiency. It depends on the nature of your problem statement you are going to choose, and what methodology you are going to adopt.

Moreover, if you need further assistance don’t hesitate to contact us for more details.