Yashwanth.

Worked on AI infrastructure and machine learning workflows by designing Linux-based compute environments, enabling scalable model training and experimentation.

• ▸Designed, trained and evaluated machine learning models using PyTorch, TensorFlow, and Scikit-learn on self-configured Linux compute infrastructure, performing data preprocessing including data cleaning, feature scaling, and dataset preparation.
• ▸Installed and configured Intel oneAPI HPC toolkit to optimize compute performance and support accelerated execution of data processing and machine learning workflows.
• ▸Built and maintained a multi-node Linux compute cluster using NFS for shared storage and NIS for centralized authentication across nodes.

Delivered end-to-end web applications for startups and small businesses across e-commerce domain.

• ▸Designed and developed a custom Odoo module for hotel review management, automating review processing workflows and reducing manual data entry by approximately 6 hours per week while improving data accuracy by 30%.
• ▸Implemented backend business logic using Python and XML to extend Odoo’s core functionality,streamlining review categorization and improving processing efficiency by 40%.
• ▸Designed and optimized PostgreSQL database queries and schema interactions to support efficient data storage and retrieval for review management workflows.

Collaborated on practical AI/ML solutions involving classification systems, applying data preprocessing, exploratory analysis, and machine learning workflows to solve real-world problems.

• ▸Performed exploratory data analysis and visualized dataset patterns using Python libraries to identify trends and improve model performance.
• ▸Built and evaluated machine learning models using Pandas and Scikit-learn, performing data preprocessing, feature scaling, and performance evaluation.
• ▸Developed a spam detection model using machine learning techniques, achieving over 80% classification accuracy through feature engineering and model evaluation.