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AI & ML Intern with less than a year in Data Visualization & NLP
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Assessing your cultural and operational fit
Aspiring AI/ML professional eager to apply my academic knowledge and programming skills in a dynamic environment. Aiming to contribute to the development of innovative solutions and gain practical experience in the field.
A.P.J Abdul Kalam Technological University
Bachelor of Technology · Computer Science and Engineering (Artificial Intelligence & Machine Learning)
September 1, 2022 – Present
ECIL
Data Visualization Intern
May 30, 2025 – June 27, 2025
Hyderābād, Telangana, India
AI-Driven Anomaly Detection and Visualization System for PLC Binary Log Dat
June 24, 2026 – Present
Built an AI-based PLC monitoring system using Isolation Forest to detect anomalies in digital and analog binary log data. The project enables channel-wise visualization and comparison of normal versus faulty operating conditions, supporting intelligent fault detection in industrial automation.
Speech to Text Converter with Sentiment Analysis
June 24, 2026 – Present
Developed a Python-based interface using Flask and Socket.io to facilitate real-time speech-to-text conversion and analysis. Integrated NLTK and TextBlob to perform automated sentiment analysis, enabling the system to detect and visualize emotional tones from both live audio and recorded files. This project showcases the integration of low-latency client-server communication with a full NLP pipeline for emotion-aware data processing.
Cultural Fit Analysis
The candidate's academic projects demonstrate an interest in AI/ML applications, aligning well with an 'AI & ML Intern' role. The diversity of projects (NLP, anomaly detection, data visualization) shows a breadth of interest within the field. However, the experience is primarily academic and internship-based, which is typical for an intern, but limits assessment of long-term cultural fit in a professional setting.
Soft Skills & Operational Fit
The candidate's project descriptions indicate an ability to work on complex technical problems and integrate various tools/libraries. The internship experience suggests an understanding of data processing pipelines and visualization. However, without psychometric test results, it's difficult to assess logical reasoning, work attitude, stress handling, or team collaboration.