Basic Level - P1
P1 is a basic level requiring little technical background, and comprising of understanding the fundamentals of an algorithm and applying it to a simple problem. In such projects you acquire basic skills like background knowledge, understanding of an existing algorithm, its parameters, tuning of the parameters and a simple application of the algorithm. P1 projects typically do not lead to a research publication and are not considerable for Bachelor thesis. However, they present an excellent opportunity to enable you to the next levels P2 and P3.
- Machine Learning
1.1. Topic Classification: Given a webpage like yahoo.com , which category/class does it belong it to?
1.2. Latent Dirichlet allocation (LDA): An advanced type of clustering (soft clustering) technique based on statistical distributions.
1.4. Expectation Maximization
- Natural Language Processing
1.5. Part-of-Speech Tagging: Automatically find out the part of speech tags in a sentence.
1.6. Named Entity Recognition: Given a sentence “Niket worked at Yahoo”, recognize entities automatically: Niket/Person worked at Yahoo/organization.
1.7. Word Sense Disambiguation
1.9. Character Language Modeling
1.10. Language Identification
1.11. Spelling Correction
1.13. Clustering: Group similar items e.g. news related to sports should automatically be grouped in one cluster.
1.14. Singular Value Decomposition
1.15. Data Mining using database queries
1.16. Interesting Phrase Detection