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Data Science with less than a year in Machine Learning and Deep Learning.
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Final year Information Technology student at KIIT University (CGPA: 8.71/10) with hands-on expertise in Machine Learning and Deep Learning. Built CNN models achieving up to 97.75% accuracy. Proficient in Python, Java, SQL, and ML frameworks (TensorFlow, Keras, Scikit-Learn). Seeking roles in ML Engineering, Data Science, or Software Development.
Kalinga Institute of Industrial Technology
B.Tech · Information Technology
August 1, 2022 – June 30, 2026
T.N.B College, Bhagalpur
Class 12th
N/A – May 31, 2020
U Girl's High School, Meharma
Class 10th
N/A – May 31, 2018
Face Mask Detection Using CNN
January 1, 2025 – Present
Developed a binary image classifier (Mask / No Mask) for real-time safety compliance monitoring. Trained with real-world data augmentation to improve robustness across varied conditions. Achieved 90.93% test accuracy using a custom CNN architecture with TensorFlow/Keras.
Dog vs Cat Image Classification
November 1, 2024 – Present
Built a CNN-based image classifier using TensorFlow/Keras with transfer learning trained on 25,000 images. Applied data augmentation techniques to improve model generalization and reduce overfitting. Optimized using Adam optimizer and cross-entropy loss – achieved 97.75% test accuracy.
Diabetes Prediction Using Machine Learning
September 1, 2024 – Present
Built and compared three classifiers – Random Forest, SVM, and Logistic Regression – on the PIMA diabetes dataset. Performed feature selection, data preprocessing, and hyperparameter tuning to optimize performance. SVM achieved the best result with 77.27% test accuracy, evaluated using Precision, Recall, and F1-Score.
Cultural Fit Analysis
The candidate's academic projects show a clear interest and focus on Data Science and Machine Learning, aligning well with the target role. The diversity of projects (image classification, medical prediction) indicates a broad interest within the field. Their self-driven learning and competitive programming activities suggest a growth mindset and initiative, which are positive indicators for cultural fit in a dynamic technical environment. However, the lack of team-based projects or professional experience limits the assessment of collaboration and workplace adaptability.
Soft Skills & Operational Fit
The candidate demonstrates a proactive approach to learning and practical application through academic projects. Their involvement in competitive programming suggests problem-solving aptitude and dedication. However, without professional experience or specific soft skill assessments, it is difficult to fully evaluate operational fit, teamwork, or communication in a professional setting.