Ankitha Reddy

- Developed user-friendly web and mobile applications using modern technologies.

- Designed clean, responsive user interfaces and improved overall user experience.

- Collaborated with the team to plan and deliver full-stack solutions for client projects.

- Participated in backend development, API integration, and debugging.

- Actively contributed to team meetings, project discussions, and code reviews.

• Developed and implemented project plans, schedules.
• Identified, tracked and resolved critical path issues.
• Designed and implemented machine learning models (e.g, LSTM, SVR) to predict the RUL of Li-ion batteries based on historical and real-time data.
• Experienced with data visualization tools (e.g., Matplotlib, Seaborn) to communicate insights and model performance.
• Achieved a 98% in RUL prediction accuracy, leading to more reliable battery life estimation and enhanced decision-making for maintenance and replacement.

• Designed and implemented a sentimental analysis model using Natural Language Processing (NLP) techniques such as text preprocessing, tokenization, and sentiment scoring.
• Analyzed data related to projects in order to identify areas for improvement or optimization opportunities.
• Utilized machine learning algorithms(e.g Random Forest, Naive Bayes, LSTM) to classify reviews based on sentiment polarity (positive, negative, neutral).
• Achieved an accuracy of 96% in sentiment classification compared to baseline models, leading to more reliable insights for business decision-making.