Shinila

Key Skills

Software

Other

Top Subject Matter

Neural networks for control applications (digit recognition and function approximation)

Top Data Types

3D Sensor

Top Task Types

Classification

Freelancer Overview

Summer Research Intern: ANN in Control Applications. Brings 3+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Other. Education includes Bachelor of Science and Master of Science, Indian Institute of Science Education and Research, Bhopal (2021) and Higher Secondary Certificate, Kendriya Vidyalaya No.2 AFS Jalahalli East Bangalore (2021). AI-training focus includes data types such as Computer Code, Programming, and 3D Sensor and labeling workflows including Computer Programming, Coding, and Classification.

Labeling Experience

Summer Research Intern (Neural Networks for Control Applications) - IIIT Nagpur

3D SensorClassification

Completed a summer research internship applying machine learning techniques to control-oriented applications. Implemented an ANN for digit recognition using binary pixel matrices and trained the model for accurate classification. Designed and trained a second ANN to approximate the cosine function, supporting control-related computation needs. • Implemented and trained an ANN for digit recognition (0–9) • Trained models for improved classification accuracy over many epochs • Built and trained an ANN for cosine-function approximation • Performed neural network validation for control-oriented usage.

2024 - 2024

Summer Research Intern: ANN in Control Applications

Other

Implemented an artificial neural network for digit recognition (0–9) using binary pixel matrices and trained it over 1000 epochs for accurate classification. Designed and trained a second ANN to approximate the cosine function for control-oriented applications. Performed iterative training, weight optimization, and evaluation to validate model performance. • Digit recognition dataset represented as binary pixel matrices • Neural network training with weight optimization over 1000 epochs • Model performance validation for control-oriented tasks • Cosine function approximation using a separately trained ANN

2024 - 2024

Education

Work History