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Machine learning and data science enthusiast with a background in computer science.
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I work mainly with Python and libraries such as NumPy, Pandas, and Scikit-learn to build and evaluate machine learning models.
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Open to machine learning and data science opportunities.
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step_prediction
step_prediction PublicExperiments with machine learning and deep learning models for physical activity classification and daily step prediction.
Jupyter Notebook 1
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Machine-Learning-with-Jadi
Machine-Learning-with-Jadi PublicHands-on implementations of machine learning algorithms including classification, regression, clustering, and recommendation systems using Python.
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Nonlinear-Optimization
Nonlinear-Optimization PublicPython implementations of nonlinear optimization algorithms including Newton method, steepest descent, conjugate gradient and Armijo line search.
Jupyter Notebook
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Exercism-Python-Track
Exercism-Python-Track PublicSolutions to exercises from the Exercism Python track.
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Data-science-algorithms
Data-science-algorithms PublicImplementations of data processing and data science algorithms based on exercises from the book "Algorithms for Data Science", using real-world datasets such as the FEC election contributions dataset.
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Mathematical-foundations-of-data-science
Mathematical-foundations-of-data-science PublicExercises and implementations related to the mathematical foundations of data science, including probability, distributions, and basic numerical algorithms.
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