About memy stats
Information About me
As a final year BTech student, I have developed a solid proficiency in Web Development, Python, C/C++, Machine Learning. I am constantly eager to expand my knowledge and stay current with the latest technologies. My portfolio reflects my dedication to learning and my diverse skill set, positioning me as a well-rounded and motivated aspiring professional.
5+
Projects
Completed
250+
solved
Problem on GFG
My Skills
My Timeline
2022 - present
Google Developer Student Club - Machine Learning and Data Science Lead
Speaker and hosted "ML Campaign"
The official event of GDSC REC Bijnor
2023 - present
Fynd Academy - Full Stack development with JavaScript
12 week training in MEVN stack technology.
Learning Git, GitHub, HTML, CSS, JavaScript, VueJS, ReactJS, NodeJS, Express, MongoDB and much more.
2016 - 2017
secondary- Vivekananda Inter College Darbara Bijnor
Percentage:- 89%
2022
Research intern- center for advanced studies aktu lucknow
Worked as a research intern under the supervision of Prof. M.K. Datta in
the field of machine learning and AI.
Worked on the project "Skin Disease Classification using Deep Learning"
My CertificatesMy Proof
Here is some Certificates that I have Achieved.
My ProjectsMy Work
Skin Disease Identification
Web application using HTML, CSS, Bootstrap, JS, Flask. Developed a Deep Learning Model that can identifies 29 types of skin diseases Model is trained and tested on DermNet Dataset and achieved 92% accuracy on test data.
Object Detection
Developed a machine learning model that can recognizes several objects with their probability from images. Uses YOLO to identify the object in images.
Human Activity Recognition
Developed a Machine Learning Model which recognizes different human activities like standing, walking, laying, etc. It is a Machine Learning Model using different algorithms like SVM, Random Forest, LDA, ANN, and XGBoost and applied Hard Voting.
Handwritten Character Recognition
Developed a GUI using Tkinter where we can write a character and this model will identify the character with probability. The model is created using CNN and trained by MNIST dataset.
Face and smile Detection
Built a machine learning model that detect face and eyes and lips from real time camera videos it uses Python , OpenCV framework.
Chatbot using Python
Build a chatbot using deep learning techniques. The chatbot trained on the dataset which contains categories (intents), patterns and responses. A special recurrent neural network (LSTM) is used to classify which category the user message belongs to and then we will give a random response from the list of responses.
Contact MeContact
Contact me here
Bijnor, Uttar Pradesh
sunyyrajput95jaun@gmail.com
+919084052063