Investigated aviation accidents using data collection and Exploratory Data Analysis (EDA) Collaborated with teams to improve safety protocols Developed strong analytical and data interpretation skills
Amit Nahum
Computer Science Student
Rishon Lezion
Summary
Final-year Data Science student with hands-on experience gained exclusively through Kaggle competitions. Built end-to-end machine learning pipelines for tasks such as image classification, tabular prediction, and time series analysis. Skilled in Python, EDA, model selection, and performance tuning. Passionate about applying data science techniques to real-world challenges and constantly improving through practice.
Overview
2
2
Languages
Work History
UFC Result Prediction Model
- Achieved a top-10 placement in a UFC fight prediction challenge, according to publicly available results
- Built a structured machine learning pipeline to predict UFC fight outcomes using historical fighter statistics, event data, and engineered features (e.g., win streaks, age/height differences).
- Integrated data preprocessing, feature engineering, model evaluation, and hyperparameter tuning.
- Applied advanced models such as XGBoost and ensemble methods to achieve strong performance.
- Ranked in the top 10 based on publicly available leaderboard results.
License Plate Price Project Competition
Kaggle
- Won 2nd place in a Kaggle competition
- Led a data analysis project involving external feature extraction, thorough data cleaning, and preprocessing.
- Applied feature selection techniques to identify the most impactful variables.
- Used clustering algorithms to detect patterns and segment data effectively.
- Developed insights to improve decision-making and enhance investigation accuracy.
Education
Bachelor of Science - Software Engineering - Data Science Specialization
Holon Institute of Technology (HIT)
Holon 04.2001 -
Skills
Teamwork and collaboration
Machine learning
Python programming
Statistical analysis
Anomaly detection
Feature engineering
Statistical modeling
Time series analysis
Preprocessing pipelines
Deep Learning
Natural language processing
Interests
Affiliations
- Languages: Python, SQL, C, C++
- Data Processing: Pandas, NumPy
- Visualization: Matplotlib, Seaborn, Plotly
- Classical ML: Scikit-learn, XGBoost, LightGBM, CatBoost
- Feature Selection & Optimization: SHAP, GridSearchCV
- Pipelines & Experiment Tracking: MLflow
- NLP: NLTK, SpaCy
- Computer Vision: OpenCV, YOLO
- Web Scraping & APIs: BeautifulSoup, Selenium, REST APIs
- Model Deployment: Flask, Docker
Timeline
Bachelor of Science - Software Engineering - Data Science Specialization
Holon Institute of Technology (HIT)
04.2001 -
UFC Result Prediction Model
License Plate Price Project Competition
Kaggle
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