Gazi K.

Key Skills

Software

CVAT

Labelbox

Scale AI

Roboflow

AWS SageMaker

Google Cloud Vertex AI

Top Subject Matter

Artificial Intelligence & Machine Learning

Computer Vision & Image Recognition

Business Intelligence & Customer Behavior Analysis

Top Data Types

Image

Video

Text

Top Task Types

Classification

Data Collection

Bounding Box

Segmentation

Entity (NER) Classification

Transcription

Question Answering

Evaluation/Rating

Freelancer Overview

Here are both fields filled out professionally: Profile Overview: I am an AI professional with a Bachelor's degree in Artificial Intelligence and hands-on experience as an AI Intern at RWS, Mumbai, where I trained deep learning models on labeled datasets for image recognition tasks and developed predictive models to inform strategic decisions. My work involved applying feature selection algorithms, conducting data analysis, and designing assessment tools to collect and evaluate data — all core components of AI training workflows. What sets me apart is a strong combination of practical experience and formal credentials, including certifications from Stanford, DeepLearning.AI, Google, AWS, IBM, and Microsoft. I bring a detail-oriented, research-driven approach to every project, with proficiency across machine learning, data annotation, and model evaluation tasks.

Labeling Experience

Predictive Model Training & Feature Annotation

TextData Collection

Annotated and structured datasets used to train AI models for predicting customer behavior and business outcomes. Tasks included feature selection, data cleaning, and labeling structured text data for model training and validation. Designed survey and assessment tools to collect additional training data. Quality measures included systematic validation of labeled outputs and iterative refinement based on model evaluation results.

2024 - 2025

Image Recognition Data Labeling & Model Training

ImageClassification

Worked on labeling and annotating image datasets used to train deep learning models for image recognition tasks. Responsibilities included reviewing and verifying labeled data for accuracy, ensuring consistency across annotation batches, and iterating on labeled inputs to improve model performance. Quality measures included cross-checking annotations against ground truth standards and refining labels based on model feedback loops.

2024 - 2025

Education

Work History