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This project is an auto-filling text program implemented in Python using N-gram models. The program suggests the next word based on the input given by the user. It utilizes N-gram models, specifically Trigrams and Bigrams, to generate predictions.
It's a python based n-gram langauage model which calculates bigrams, probability and smooth probability (laplace) of a sentence using bi-gram and perplexity of the model.
Advance information retrieval system that combines advanced indexing, machine learning, and personalized search to enhance academic research and document discovery.
Detect the text language automatically using a bigram model, Support Vector Machines, and Artifical Neural Networks. The model is trained using the WiLI-2018 benchmark dataset, and the highest accuracy achieved on the test dataset is 99.7% with paragraph text.
Final year major project on big data analysis of instacart dataset and finally Product Bundle Recommendation using pyspark(for clustering) and bigram for recommendation
We designed an Information Retrieval system based on Vector Space model in python. We Also have implemented Bi gram Indices for Phrasal query search and Champion List retrieval. We also compared time of whole retrieving in our project report.
First Proper (formal) piece of Java software I created. It focuses on 5 different techniques of scoring documents based on queries. It also includes the code I used on AWS for a bigram model and predictions.