alexandruhau's Projects
Hello!
Machine Learning jupyter notebooks from the School of Physics course "Data Analysis and Machine Learning" with my solutions are shown. The Autoencoder part is shown.
The brownian (random motion) of milk colloidal particles in a sample of water has been analysed in Python. From the image processing algorithms, the diffusion coefficient has been worked out.
My Master's Thesis approached the implementation of ANNs in the Tracer Kinetic Modelling technique used in DCE-MRI. An MLP architecture model was analyzed and improved.
Machine Learning jupyter notebooks from the School of Physics course "Data Analysis and Machine Learning" with my solutions are shown. The Decision Tree part is shown.
Machine Learning jupyter notebooks from the School of Physics course "Data Analysis and Machine Learning" with my solutions are shown. The Deep Learning part is shown.
The Game of Life model proposed for the cellular reproduction for the first time in 50's and 60's is implemented. For this model, any cell with less than two or more than three alive neighbors becomes dead. Moreover, any dead cell with exactly three neighbors alive becomes alive at its turn.
Code for "Machine Learning for Physicists 2020" lecture series
This repository contains Python Jupyter Notebooks from the Introductory Applied Machine Learning course from the University of Edinburgh, on the academic year 2018-2019. Both my code and the solutions are attached, in order to highlight similarities and differences in the problem solving process.
The repository implements the numerical method for building the Mandelbrot set. The overall Mandelbrot manipulation highlights current mathematical techniques used in Complex Analysis and Calculus.
The coursework on Fourier Analysis from the Numerical Recieps course from the School of Physics and Astronomy - University of Edinburgh - is shown.
Coursework for the Modelling and Visualization in Physics course: Monte Carlo Simulations are performed in order to investigate the laws in Statistical Physics.
This repository is for coding activities developed in Jupyter notebooks using the Noteable platform (www.noteable.edina.ac.uk) for Scottish teachers and learners. These materials were developed between February and May 2021 and cover topics from the SQA curriculum in Computing Science, Mathematics, Statistics and other fields involving data analysi
My internship conducted during June - September 2022 at CERN is presented. The project approached the integration of a pre-trained 3D-GAN into the Monte Carlo toolkit GEANT4.
The project approaches the numerical estimation of the electric potential and field from a point charge in 3D space, as well as the magnetic vector and potential from a wire of some given current density. The Jacobi and Gauss-Seidel algorithms are implemented for the time-evolution of the system. For the latter method, the over-relaxation parameter has also been estimated through time convergence analysis.
This repository contains the project conducted during my internship in June-September 2021. I conducted Monte Carlo Simulations on GEANT4 and ROOT to compare the efficiency of a PET-Scanners at the lengths of 15cm and 2m.
In this repository, I have implemented the N-Body algorithm for the Solar System and plotted the celestial bodies on an interactive animation. The number of planets, as well as their mass, distance with respect to the Sun and even the colors can be changed. The overall energy of the system has been plotted in order to check the validity of Newton's and Kepler's Laws.
The coursework from the Numerical Recipes course from School of Physics and Astronomy is shown. The project approaches the Finite Element Method for implementing the Schrodinger Equation in ion trapping. The spectral method algorithm is used as well.
The repository implements the traffic flow through basic Monte Carlo Simulations. Additional probabilities are set for previous moving cars and stationary cars. The mean speed as function of time is worked out.
This program implements the spread of disease through the probability of getting susceptible, infected and recovered. Flu and influenza are the most known example obeying this behaviour. The whole spread is simulated on Python, on the matplotlib library.
This repository analyses the efficiency in radiation shielding of lead, steel and polyethylene against galactic cosmic rays (bosons and fermions at high energies).
The project yields the dispersion between samples of water and oil, as the free energy of the system is minimized in time. The boundary phase state between the two states also decreases in time.
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