Aman Kumar
@amankumar19
Machine learning engineer focused on predictive models and deep learning.
What I'm looking for
I am a machine learning engineer with hands-on experience building predictive and deep-learning models for real-world problems such as fake news detection, maternal health risk prediction, breast cancer classification, and fraud detection.
I have completed internships where I designed end-to-end ML solutions: from EDA and feature engineering to model selection and evaluation using scikit-learn, XGBoost, LightGBM, CatBoost, TensorFlow and Keras, and addressed class imbalance with SMOTE.
I deliver reproducible work using Jupyter/Colab and Git, and I am passionate about continual learning, competitive programming, and applying data-driven solutions to healthcare and finance challenges.
Experience
Work history, roles, and key accomplishments
Data Science Intern
Syllogistek Pvt. Ltd.
May 2025 - Jun 2025 (1 month)
Designed and implemented a hypothyroid prediction model using ensemble techniques, performing EDA, feature engineering, SMOTE balancing, and model comparison to optimize performance.
Machine Learning Intern
Silicon University
Aug 2023 - Sep 2023 (1 month)
Worked on real-world ML problems including fake news detection and maternal health risk prediction, building and tuning supervised models to improve predictive performance.
Education
Degrees, certifications, and relevant coursework
Silicon University
Bachelor of Technology, Computer Science and Engineering
2022 -
Grade: CGPA: 8.08
Activities and societies: Machine Learning Intern; projects in CNN-based image classification, thyroid prediction, and fraud detection.
Pursuing a BTech in Computer Science and Engineering with a CGPA of 8.08, focusing on machine learning and applied projects.
Marwari College
Intermediate (JAC), Intermediate
2019 - 2021
Grade: 76.2%
Completed Intermediate (JAC) with 76.2% focusing on foundational coursework prior to undergraduate studies.
Indumati Tibrewal Saraswati Vidya Mandir
Matriculation (JAC), Matriculation
Grade: 91.4%
Completed Matriculation (JAC) with 91.4% demonstrating strong academic performance at the secondary level.
Availability
Location
Authorized to work in
Social media
Job categories
Skills
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