Tarun S.

Key Skills

Software

Data Annotation Tech

Top Subject Matter

Machine learning for dementia detection/disease detection

Dementia detection using machine learning

Top Data Types

Image

Text

Audio

Top Task Types

Diagnosis

Transcription

Data Collection

Evaluation/Rating

Freelancer Overview

Machine Learning Intern — Verzeo-Microsoft (11/2020 - 12/2020). Brings 1+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Don't disclose and Other. Education includes Bachelor of Technology, Reva University (2021) and N/A, Narayana Junior College (2016). AI-training focus includes data types such as Medical and DICOM and labeling workflows including Diagnosis.

Labeling Experience

Machine Learning Intern — Verzeo-Microsoft (11/2020 - 12/2020)

Don't discloseDiagnosis

The Machine Learning Intern role involved working on AI/ML tasks related to disease detection, which typically require preparing and transforming labeled medical data for model training. The internship focused on turning raw datasets into forms suitable for machine learning assumptions and evaluation workflows. This experience aligns with AI training where labeled examples are used to build predictive models and validate performance. • Likely supported dataset preparation and label formatting for ML training pipelines • Worked on model training readiness by transforming raw data to match algorithm requirements • Collaborated on applying machine learning concepts to detection/classification use cases • Used programming tools commonly required for ML experimentation and iteration

2020 - 2020

Project: DementiaDetection Using Machine Learning Algorithms (Tools: Jupyter Notebook, PyCharm; Language: Python)

OtherDiagnosis

The Dementia Detection project used machine learning approaches to support disease detection, which typically depends on labeled medical or diagnostic datasets. The work included applying data transformation steps so the dataset could conform to the assumptions of the machine learning algorithms. This is consistent with AI training workflows where labeled data underpins model development. • Applied machine learning algorithms for dementia detection use case • Transformed raw data to satisfy model/algorithm input assumptions • Prepared data for training by conforming it to expected formats • Developed the project using Python-based ML experimentation

2020

Education

Work History