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Projects

Real-TIme Face Recognition based attendance API

Trained multiple models such as VGG, FaceNet, Deepface and others on custom data. Chose the best model(FaceNet) and deployed it using FastAPI.

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Yield prediction based on real-time crop data

The project deals with analyzing the trends in crop yield data of Telangana from the years 2016-2019 and building a suitable ML model with the factors affecting to predict the total yield. A web application was also built to demonstrate the working of the model.

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Rural Health Care Application

The real time data of medical staff was collected and analyzed. A ML based web application was built to predict the number of staff that can be allocated at medical facilities all over India.

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Atrial Fibrillation detection Using ML

This project uses ML to detect if a person has Atrial Fibrillation or irregular heartbeats.

The project takes an ECG signal of heart as input which is converted to relevant features using HeartPy module.

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Restaurant Cuisine Demand Predictor 

This project is implemented using ML to predict the demand of the given dataset concerned with reviews of customers of a food company. The data was analysed using python and certain trends, findings were discovered in the process. 

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Uber Data Analysis

The real-time data collected by Uber was analyzed using python and jupyter notebook. The process of identifying the populated areas using clustering and Folium python module was visualized. A predictive model was trained to further understand the data.

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University admit eligibility predictor

The project is implemented using a Machine-Learning model that predicts whether the user is eligible for an admission in the selected rated universities with provided details such as marks and others. The algorithm works in such a way that when the user provides the details such as (GRE Score, TOEFL Score, University Rating, SOP, LOR, CGPA, Research) the percentage of chance of admit is displayed.

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ORGANIZATIONS

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© 2022 by Ashwin Kumar Sangareddypeta.
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