IMDB Top 1000 Analysis
Conducted comprehensive data analysis and visualization of IMDb's Top 1000 movies, extracting insights into film trends and audience preferences. Data processing and visualization performed from Jan 2023 to May 2023.
Ashpak Pendari
AI Agentic Workflow Freelancer
GadagArtificial Intelligence and Machine Learning
3roles
19skills
2education
1credentials
About
AI/Machine Learning Engineer passionate about applying AI to real-world problems, developing scalable solutions, and optimizing models for production environments.
Experience
Freelancer - Project Nebula
SOUL AI
Jan 2025 - Present
Working on an AI agentic workflow for SOUL AI.
Training Intern
AWIGN Enterprises Pvt. Ltd. - Neuralace AI
Dec 2024 - Mar 2025
Collected and prepared diverse multimodal datasets, including images, videos, and audio, to train AI systems assisting visually impaired individuals. Ensured ethical compliance, maintained high-quality annotations, and applied data augmentation techniques to enhance model performance.
Machine Learning Intern
Nov 2023 - Dec 2023
Worked on Netflix analysis using exploratory data analysis and clustering of similar content by matching text-based features. Also worked on rental bike regression analysis and developed a customer churn prediction model using Random Forest, achieving 90% accuracy and a 15% reduction in churn. Deployed the model with Flask for real-time predictions.
Education
Karnataka State Rural Development And Panchayat Raj University, Gadag
Master of Science, Computer Science (Data Analytics)
Dec 2022 - Nov 2024
JT College, Gadag
Bachelor of Science
June 2017 - Sep 2021
Skills
Data analysis and visualizationWeka ExplorerPythonPyTorchPower BIAWSMicrosoft ExcelTensorFlowAI prompt generationNeural networksSQLAI tools specialistCNNYOLOFlaskRandom ForestClusteringFeature engineeringData preprocessing
Projects
Rural Immersion
Conducted rural surveys, data collection, analysis, and visualization, along with spreading awareness, from May 2023 to Nov 2023.
Vehicle Taillight Detection Using Deep Learning
Developed a real-time deep learning model for vehicle taillight detection, optimized for diverse conditions to enhance autonomous driving safety. Used Python, TensorFlow, PyTorch, CNN, and YOLO. Optimized the data preprocessing pipeline, reducing preparation time by 30%, and engineered features that improved accuracy from 85% to 92%.
Project Nebula
AI agentic workflow for SOUL AI.