Shravani has completed her undergraduate from Pune University and later joined Schlumberger as Technical monitoring Analyst. She is currently active on Kaggle and Machine hack. She wants to pursue graduate degree in the field of Data science. As an undergraduate student at her college, she carried out research in Machine learning for medical domain. She loves participating in hackathons and has great love for innovation and entrepreneurship as well.
Detection of lung disease using CXR images.
One of its kind Code in Hindi Platform
Detecting the real and fake news using variants of BERT
Detection of ocular diseases using Fundus images
User activity recognition using real time sensor data
Crop weed detection for sesame plants
simple game where multiple enemies follow the user and die if they collide.
Got first prize in the project competition hosted by CSI chapter of PCCOE
Hackathon hosted by PCMC to welcome the Ideas and innovation for Smart city. Our zero cost solution received special appreciation from the juries and First runner up prize from the health and sanitation domain. Also filed patent on the same.
"SYSTEM AND METHOD FOR LOCATING AND RESERVING RESTROOMS" reached round 2 of AIC
"Self-sustainable Cloud Platform For Data Management And Extraction Of Actionable Knowledge For Smart Healthcare Industry" got selected among top 200 submissions among the solution pool of 7000.
Genpact challenge was hosted on Machine hack platform. The problem statement was to predict lap time of racing cars depending on numerous factors including weather. Task: Regression; Goal was to minimize RMS error. In top 4% on the final leaderboard.
This Hackathon was hosted by ZS associates. The multiclass classification was to predict the outcome state of animal from animal shelter. In the Top 10.
Organized on Machine hack platform; Problem statement was to predict given person is a loan defaulter or not. Task: Binary classification, Goal was minimized logloss. Rank 46
"Uhack Sentiment2.0: Decode Code words" by Merkel was organized on Machine hack platform; A review dataset was given and the problem was to classify a given review among 14 different label; Task: Multilabel Classification; Rank 5
Participated in “GUINNESS WORLD RECORD FOR LARGEST DISTRIBUTION OF SAPLINGS”, by NSS. (June 23, 2019)
This application is aimed at providing diagnosis assistance to the doctors dealing with lung diseases. By uploading single X-ray Image, the application can predict range of lung diseases including COVID19, Pneumonia, Effusion, Atelectasis and many more.
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A single-player game created with G develop and deployed on Netlify, in which you are pursued by multiple enemies and must avoid colliding with them. The difficulty level of the game increases as the player keep scoring. The score depends on the time length you survive and enemies you kill before dying. The white light is the proximity area using which the enemies can sense and start pursuing you. The player has to kill the enemies by dodging and drifting them into themselves. The controls are simple four arrow keys on the keyboard.
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one of a kind code in Hindi platform which enables users to Code in native Hindi language. It is a wrapper around normal python which converts a
code written in Hindi to English and executes it.
#अब कोड लिखें हिंदी में
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A BERT based tool to classify a piece of text into fake or real, implemented using Simpletransformers and Huggingface. Our approach takes the stance detection, text and emotional aspect of given text into consideration. It takes the text as input and comparing its stance with various trustable resources available online.
An easy to use AI enabled tool for detection of ocular disease. After giving a fundus image as input the classifier can predict whether the image is of left or right eye. It further tells whether it is a normal eye or it is suffering from any eye disease like Cataract, Glaucoma, hypertension, Myopia and AMD.
SensorAI is a tool to detect the activity of user using the timeseries data coming from smart phone sensors including accelerometer and gyroscope sensors (attitude, gravity, user Acceleration, and rotation rate). The deep neural network can detect activities like walking, standing, sitting, upstairs, downstairs etc. The model is trained on sensor data of IPhone6s.
A Crop weed detection system for identifying the unwanted plants called weeds from the soybean crop. The classifier neural network can identify the weed, crop and soil from a given image. This model can be used in the system where we want to automate the task of spraying weedicides and also save the crops from unwanted spraying of harmful chemicals.
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