ANSH SHARMA

I am an enthusiastic individual with a strong desire for continuous learning and personal growth.I approach each opportunity as a chance to expand my knowledge and skills. Whether it's acquiring new technical proficiencies or developing a deeper understanding of industry trends, I actively seek out opportunities to enhance my expertise.

Throughout my background, I have demonstrated a team oriented mindset and a commitment to collaboration. Currently Learning MERN Stack and Deep Learning.

• IBM Machine Learning.
• Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization.

(A)Major

(I)  Medical Website including Chatbot (AI Doctor) in IInd year

I played a pivotal role in shaping both the frontend and backend aspects of the platform, offering valuable insights and contributions throughout the project lifecycle. 

• Implemented a chatbot powered by Faiss and Flask to facilitate intuitive interactions with users.
• Utilized natural language processing (NLP) to understand and respond to user queries effectively.
• Integrated Faiss to enable disease prediction based on user-provided symptoms or medical history.
• Implemented backend functionality to retrieve medication information from databases or APIs.

(II)  Simplifire(fire dectection system using camera)

Description: Developed a computer vision-based fire detection system utilizing Python and OpenCV to detect fire outbreaks through a webcam. The system implements various actions upon detecting fire, including notifications, system shutdown, and geographical information retrieval.

• Languages & Libraries: Python, OpenCV (cv2), winsound, os, time, smtplib, pyttsx3, email.message, requests, json, urllib.request.urlopen.
• Tools & Technologies: Cascade Classifier for fire detection, SMTP for email notifications, IP-based geolocation services.
• Fire Detection: Utilized a Cascade Classifier for real-time fire detection through a webcam.
• Email Notification: Configured the system to send email alerts (commented out in the script) using smtplib and email.message.
• Geographical Information: Retrieved and printed geographical location (longitude and latitude) based on the user's IP address using requests and json libraries.

(B)Minor

(i) Zipit: Description- Developed a file compression and decompression tool combining C++ for backend processing and Python for a graphical user interface, providing an efficient and user-friendly experience.

(ii) Sleep Study: exploring the relationships between sleep patterns, daily habits, and self-reported tiredness levels. The project aims to uncover insights into the factors influencing tiredness and contribute to a better understanding of the impact of sleep on overall well-being.