Machine Learning & Data Science Notebooks
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Updated
May 24, 2024 - Jupyter Notebook
Machine Learning & Data Science Notebooks
My PhD thesis
PHP MVC framework for bulding web applications
R interface to the ANTs biomedical image processing library
Matrix decomposition algorithms including PCA (principal component analysis) and ICA (independent component analysis)
Abstract thinking patterns and problem decomposition / solving strategies
Исследуется тензорный метод декомпозиции и предсказания временных рядов tSSA
Cross-platform .NET library for digital signal processing. Fast and optimized
Two CNN-based models for pre-processing the Full-waveform LiDAR signals.
Shape analysis has become of increasing interest to the medical community due to its potential to precisely locate morphological changes between healthy and pathological structures. SPHARM-PDM is a tool that computes point-based models using a parametric boundary description for the computing of Shape analysis.
Generic tool dedicated to fit spectra in python
🎓 Undergraduate thesis source code: decomposed the dunder-mifflin-infinity app into 4 microservices. Built-in Spring Boot with Eureka Server.
Python libraries for soft sensing applications.
Python implementation of Empirical Mode Decompoisition (EMD) method
TensorLy: Tensor Learning in Python.
R library for the Life Expectancy Monitoring Tool
Use IBM API for anomaly detection in time series data, visualisation, seasonality with statsmodels decomposition and Fourier analysis, K-Means clustering
TeMD(Thermal extreme, Microbiome, and Decomposition) with DEMENTpy at Walker Branch Watershed, Oak Ridge, Tennessee
Forecasting Wine Sales of Two Different types of Wine. After thorough Data Analysis, different models have been used and tested such as Exponential Smoothing Models, Regression, Naive Forecast, Simple Average, Moving Average. Stationarity of the data is checked. Automated Version of ARIMA/SARIMA Model built. Comparison of Models.
A system of linear equations solver with a parallel LU Decomposition algorithm implemented using Pthreads at its core. C/C++ implementations with and without pivoting. Thoroughly documented and benchmarked on an intel linux system and a macbook pro with Apple Silicon M3pro chip. This project was developed as a project at Portland State University
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