rajeshwarichandratre
Data Science Intern at SJSU | Software Engineer Intern at Viome | Masters' in Computer Science from San Jose State University | Software Developer at Cybage
ViomeSan Jose, California, USA
Pinned Repositories
cs265_hilly
Encryption, and decryption of ‘Hilly cipher’ which is similar to Hill cipher along with an attack on the cipher.
doodle-recognition
A doodle recognition system based on the Google's Quickdraw challenge developed using python, depthwise CNN and a deep learning approach, MobileNet.
image-portal-web-app-using-aws
A Cloud-Based Image Sharing Platform - A distributed, scalable, fault-tolerant and highly available cloud-based platform developed using AWS
rajeshwarichandratre.github.io
Use this template if you need a quick developer / data science portfolio! Based on a Minimal Jekyll theme for GitHub Pages.
survival-of-passegers-on-titanic
A machine learning model to predict the survival rates of the passengers on the Titanic ship. Algorithm Used: SVM Accuracy obtained - 97%
toxic-comment-classification
A machine learning multi-label classification model to identify various types of toxic comments posted on social networking sites. Used and compared different machine learning algorithms such as SVM, KNN, XGBoost, LSTM, and NLP using TF-IDF, Glove. Achieved an average accuracy of 90%.
rajeshwarichandratre's Repositories
rajeshwarichandratre/cs265_hilly
Encryption, and decryption of ‘Hilly cipher’ which is similar to Hill cipher along with an attack on the cipher.
rajeshwarichandratre/doodle-recognition
A doodle recognition system based on the Google's Quickdraw challenge developed using python, depthwise CNN and a deep learning approach, MobileNet.
rajeshwarichandratre/image-portal-web-app-using-aws
A Cloud-Based Image Sharing Platform - A distributed, scalable, fault-tolerant and highly available cloud-based platform developed using AWS
rajeshwarichandratre/rajeshwarichandratre.github.io
Use this template if you need a quick developer / data science portfolio! Based on a Minimal Jekyll theme for GitHub Pages.
rajeshwarichandratre/survival-of-passegers-on-titanic
A machine learning model to predict the survival rates of the passengers on the Titanic ship. Algorithm Used: SVM Accuracy obtained - 97%
rajeshwarichandratre/toxic-comment-classification
A machine learning multi-label classification model to identify various types of toxic comments posted on social networking sites. Used and compared different machine learning algorithms such as SVM, KNN, XGBoost, LSTM, and NLP using TF-IDF, Glove. Achieved an average accuracy of 90%.