Implemented the Naive-Bayes Classifier to detect email spam using Bernoulli, Gaussian Random Variable, and the Histogram Method. Performed Machine Learning on training data set to calculate probabilities of certain features being spam and predict spam on testing data.
In this project using python I implemented the pagerank algorithm and found out pageranks of 183811 web pages and then did a brief analysis of the results.
Developed a search engine using Vector retrieval, Language Model and BM23 and analyzed the results to determine which model gives better results for different types of queries
In this project I created a tunnel using TUN command between machine 1 and and machine 3. Machine 3 used to send data for machine 2 which was intercepted by machine 1 and then send to machine 2 by using raw sockets.Machine 2 used to get reply from machine 2 which it used to send back through the tunnel to machine 3
The algorithm Kekre's Median Codebook Generation (KMCG) has been efficiently used for image processing but had not been tried for processing audio signals. We designed a system which collected voice samples of people to generate a codebook of their voice charachteristics with the help of KMCG. Once the Codebook was generated the system compared the voice signal of the user with the already generated Codebook thus carrying out the feature matching process with the help of Euclidean distance. We used MFCC for extracting the features of the voice samples and Vector Quantization to create a codebook and for the vector matching.