• Overall 4+ years of experience working as a Full-Stack developer.
• Having strong technical skills as well as excellent interpersonal skills, I am eager to be challenged in order to grow and improve my
  professional IT skills gained through experiences in this industry.
• Hands-on experience with Generative AI, Machine Learning.
• Intermediate hands-on experience with Stable Diffusion models and algorithms.
• Experience with natural language processing (NLP) techniques
• Proficient in programming languages including Javascript, Typescript, Python, and Nodejs.
• Strong problem-solving and analytical skills
• Good communication and teamwork abilities
• Familiarity with cloud computing platforms, such as AWS or Google Cloud

Libraries & Languages: Python, React JS, Next JS, Javascript, Typescript, Scikit-Learn, TensorFlow

Database: MySQL, MongoDB
APIs: REST, Graphql
ML and AI: Deep Learning, Codex app development, DALL·E app development, Vector DB, Lang Chain, WhatsApp Chatbot, Python libraries and development, Stable Diffusion Models
Others: Auth0, Error handling

Torri.ai:

Description: This is a SAAS chatbot solution where users can create chatbots from scratch using their custom data sources with no coding knowledge. Users can create and integrate the chatbots with Website, Whatsapp, Telegram and Slack.
Technologies Used: NextJS, MongoDb & MySQL, OpenAI, Langchain, Pinecone

Ai-Interview:

Description: This tool helps candidates to prepare for an Interview. Candidates have to provide the job title and job description for the interview they are applying to. ChatGPT shall act as an interviewer and ask questions based on the JD and JT provided by the candidate in the previous step.Candidates can provide answers verbally. The tool shall convert it into transcript and provide analysis. Based on the answers, ChatGPT shall generate a detailed feedback and guidelines to provide better answers.
Technologies Used: Reactjs, Python, MongoDb, OpenAI ChatGPT

Health Monitoring System for Elderly Care:

Description: This project involves creating a health monitoring system for elderly individuals living independently. Machine learning algorithms are employed to analyze data from wearable sensors, such as heart rate monitors and accelerometers, to detect anomalies and predict potential health issues. Stable diffusion techniques are utilized to provide accurate and timely alerts while minimizing false alarms.
Technologies Used: Python, scikit-learn, TensorFlow, wearable sensor data processing, anomaly detection algorithms, Stable Diffusion Models (SDMs)