AnushreeAnkola

AnushreeAnkola's Stars

• AnushreeAnkola/Early-Sepsis-Classification-Analysis

  Analysis and prediction of Sepsis in patients

  Language:Jupyter Notebook162

• AnushreeAnkola/Time-series-forecasting-champagne-sales

  Language:Jupyter Notebook1

• AnushreeAnkola/Scaling-MiniTwit-using-RestAPIs

  Adding Web Service API to MiniTwit

  Language:Python1

• AnushreeAnkola/Sign-Language-Predictor

  Implement a web application that translates American Sign language and displays the prediction results as text to the user. The project also fulfills the task of real time data collection from the web camera, connected to the PC. The sign captured from it is sent through the trained model to predict the nature of the sign.

  Language:Python1

• AnushreeAnkola/FindASportPartner

  web application to facilitate people in finding partners to play a sport. Partner search is based on individual preferences. (Favorite Sport, Location, Available Time Schedule, Sport Expertise level, Age, Sex, and etc.).

  Language:PHP13

• AnushreeAnkola/Multichannel-EEG-based-Principal-Component-Sentiment-Disorder-Detection-model

  Emotion or sentiment is a strong feeling derived from one's circumstances, mood, or relationships with others. It plays an important role in the interaction between humans. There are a number of techniques for the detection of human sentiments using channels such as voice and facial expressions. Many a times these channels can be faked with or without the knowledge of the person. Therefore, making use of a reliable system such as Electroencephalography to record physiological signals becomes vital. The data is collected from a publicly available platform, which is a multichannel (32 Channel) data taken from 14 subjects (7 males/7 females) acquired using the NeuroScan software. The subjects undergo an experiment which gives the EEG signals. The data necessary is derived from these signals. The project is divided into two stages. The first stage of the project is to infer all the necessary information from EEG signals, reduce them to our requirements and identify the sentiment of a subject. Two models are built in this stage. PC-RoDx (Principal Component-Reduction of Dimensions) uses Principal Component Analysis and DEAn (Detection of Emotions and its Analysis) uses Sentimental Analysis. The second stage of the project involves optimizing the models to reach at the best solution. Another model called HOPe (Highly Optimized Performance) is built. This uses High Performance Computing for arriving at the most accurate and optimal model for sentiment detection. The main objective of this project is to find the sentiment of the subject after applying the models PC-RoDx, DEAn and HOPe on the obtained data.

  Language:R2

• AnushreeAnkola/Hamming-Codes

  The main objective is, detection of single bit error, burst error and to correct by using the suitable Methodology (by hamming distance concept). The purpose of this project is to visualize unreliable Transmission of data during the transmission from encoder to decoder. It involves block coding, finding the hamming distance between to existing code words, redundancy, error correction, parity check code.

  Language:C++2

• AnushreeAnkola/Binary-Classifcation-of-presence-of-water-bodies

  Language:Python1