Hi, I am Abhishek Revaskar
Welcome to my portfolio.
Explore this page to know more about me.
| Year | Degree/Certificate | Institute | CPI/% |
|---|---|---|---|
| 2021-present | M.Tech/ CSE | Indian Institute of Techonogy, Kanpur | 8.57/10 |
| 2017-2021 | B.E./ IT | Goverment College of Engineering, Aurangabad | 7.26/10 |
| 2015-2017 | HSC(XII) | Rajeshwar Union Jr. College, Badnera | 92.00% |
| 2014-2015 | SSC(X) | Suman High School, Surat | 86.00% |
Developed a Web Application to detect whether an Android application is benign or malicious. Extracted key features from the decompiled APKs, like Android Permissions, API calls, and OPcode sequences. Machine Learning and Deep Learning models were trained on these features with accuracy upto 94%.
Github
Developed a web application to summarize a Ramayana event based on the user query. Used GloVe, FastText, and Sentence-BERT word embeddings to find the sentence vectors and generated the event summary by ranking the most similar sentences using TextRank Amdorithm and clustering.
Github
Analysed the movement of major indicators of the top 100 cryptocurrencies, like Market Capitalization, Volume, Returns, etc.Scraped cryptocurrency data, performed data cleaning and data visualization and analysed various features, like moving averages and volatility, and performed risk analysis using Z-score.
Github
Analysed the spread of Covid-19 across different levels of the country from the Covid-19 dataset. Preprocessed the unstructured Covid-19 dataset and used it to predict some qualitative insights like vaccination rates, spreading rates, hotspot regions, and peaks for every district and state in India.
Github
Tokenized and stemmed the language corpus and implemented Boolean Retrieval System, TF-IDF, and BM25 IR systems. Evaluated word similarity scores using Pre-trained word vectors like GloVe, CBOW, Skipgram, and FastText . Used N-grams to determine the most common words, characters, and syllables in Indian languages.
Github
