AI Associate @SynaptyX AI || 2 x Microsoft Certified || Building The Next-Gen AI Powered Data Accelerators

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Sudarsanam Bharath  • Peerlist

Welcome to DiabSynth, the frontier of predictive health analytics, where the synergy of algorithms and empathy transforms the very fabric of diabetes care. Within our consortium, trailblazing minds, visionary engineers, and dedicated healthcare aficionados unite with unwavering determination. Our collective mission is nothing short of redefining the boundaries of healthcare technology, ushering in a new era in diabetes management that transcends the ordinary.

Predictive Health Analytics for Diabetes Risk Assessment and

DeepTumor is a brain tumor segmentation and classification project aimed at developing a deep learning model with over 1 million parameters using TensorFlow. Our model will be powered by fresh data images and optimized for accuracy and efficiency. We have employed green computing practices to ensure that our model contributes to Sustainability. One of the key features of DeepTumor is the development of a User Interface that enables easy interaction with the model. Users will be able to input patient details, and within seconds, the system will generate reports on tumor detection and classification. These reports will be delivered via email or SMS for user convenience. Our project will be an important tool for healthcareprofessionals to improve the 
diagnosis and treatment of brain tumors. The high accuracy and efficiency of our deep learning model will ensure that patients receive timely and accurate information, leading to better patient outcomes. We believe that our focus on sustainability combined with the latest deep learning technology will make DeepTumor a valuable and innovative contribution to the healthcare field.

Segmentation and classification of Brain Tumor aka DeepTumor

Sentiment analysis using Azure Cognitive Services enables automatic identification and classification of emotions in text data, providing insights for better decision-making. The purpose of sentiment analysis is to identify the sentiment or polarity of the text, whether it is positive, negative, or neutral, it is a common use case for natural language processing (NLP) and is used in various applications such as social media monitoring, customer feedback analysis, and market research.

Sentiment Analysis Using Azure Cognitive Services aka EMOSEN

Developed a solution for job seekers on LinkedIn. This automation tool streamlines the job application process and saves valuable time for job seekers by automating repetitive tasks and allowing them to focus on what matters most - securing

Applicant Express

Kitchen Inventory Tracker

MLRCIE Website

Developed a birthday mail bot using Python, SMTP, and cloud technology. The bot uses the recipient's information that is stored in a data frame and automatically sends personalized birthday emails to all of my friends using the SMTP library

PartyPal

Sentiment analysis using Azure Cognitive Services enables automatic identification and classification of emotions in text data, providing insights for better decision-making. The purpose of sentiment analysis is to identify the sentiment or

Sentiment Analysis Using Azure Cognitive Services

Developed a stock prices and news messaging bot using Python, Twilio, and cloud technology. The bot sends daily updates to users on the latest stock prices and news, allowing them to stay informed on market trends and make informed investme

StockWave-1

Developing the Stockwave1 by upgrading the messaging capability to a cross platform flutter application with further more features like rich user interface, future prediction of the stock prices with an visual representation using analysis 

StockWave-2

Developed a portfolio website during my internship as a web developer. The portfolio showcases my skills and projects using HTML, CSS, and JavaScript. The website is designed to be visually appealing and easy to navigate, highlighting my ab