Shubham goyal's repositories
Sentiment-Analysis-On-Hindi-Reviews
We have used 250 sentences of movie reviews available for research from IIT bombay and also crawled and manually annotated 750 reviews from jagran.com, In total 1000 reviews. After preprocessing the dataset, We generate the featureset as a vector-based approach using Term frequency, tfidf for unigrams and bigrams. Then we used three approaches to predict the sentiment of a review. Approaches used are Resource based, In-language semantic analysis and Machine Translation based semantic analysis.
Deep-learning-specialization
Deep learning specialization couse material of coursera
FinalYearProject
Semantic analysis on hindi reviews
MLnanodegree
Ml nanodegree program projects and solutions
Review-analysis-using-Topic-modeling-and-sentiment-mining
In this project, latent dirichlet algorithm is applied on dataset of yelp reviews to extract topics that are most discussed by users to give better insight about business products. Linear regression is used to predict the biasedness of ratings and Sentiment analysis is also done to check the comparability of reviews with their ratings.
Hello-world
He this is about a project.
HotelManagementSystem
In this project Management of rooms of hotel according to preferences in done.
Sentinel
A powerful flow control component enabling reliability, resilience and monitoring for microservices. (面向云原生微服务的高可用流控防护组件)