About
Skills & Expertise
Java
Python
R
C
C++
CSS
MySQL
MongoDB
GCP
AWS
AZURE
PyCharm
R Studio
Tableau
Google Colab
OpenCV
Machine Learning
Deep Learning
Computer Vision
Data Science
Data Analysis
Transfer Learning
Recurrent Neural Networks
MobileNet
LSTM
Kaggle
Traffic Sign Detection
Object Recognition
Music Recognition
Mobile Price Range Prediction
Research Interests
Problem Solving
Teamwork
Leadership
Connect With Me
Experience
Machine Learning Trainee
Worked as a Machine Learning Trainee; handled on real -time datasets like Mobile Price Range Prediction IS2020 on Kaggle ; and real-time datasets like MNIST, fashion -MNIST, CIFAR100, Titanic Used Python language in Google Colab as well as PYchram and Jupyter notebook Undertook Computer Vision project using OpenCV developed using Python and Caffemodel dataset for object recognition
Education
Sandip University
DAV Public School
Naman Vidya School
Projects
Music Recognition
Aim: To d evelop a machine that builds the tunes of a song by learning from the given songs input and builds a song of it's own Used LSTM model of Deep Learning in Python for automatically mixing the music data in sequence It randomly selects an array of values from the song model and chooses the maximum probability value from it and appends it to the final model.
Object Recognition
Aim: To build a computer vision for detecting objects in front of the camera by using OpenCV A Computer Vision module was developed using Python language and Caffemodel dataset for object recognition Real-time object detection is a task of doing object detection in real -time with fast inference while maintaining a base level of accuracy
Traffic Signs Recognition Systems
Aim: Trafc sign detection and recognition have received increasing interest in the last few years. This was an attempt to make a self -learning system that can itself understand and interpret the meaning of new traffic signs German Traffic Signs Detection Bench mark dataset was used with an approach to efficiently detect and recognize traffic signs in real -time, taking into account the various weather, illumination, and visibility challenges through the means of transfer learning Tackled the traffic sign detecti on problems using multi -object detection systems such as Recurrent Neural Networks, combined with various feature extractors, such as MobileNet
Certificates & Licenses (3)
Data Science and Python
Java Level 1
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