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🚀 A library designed to facilitate work with probability, statistics and stochastic calculus
Probabilistic Deep Learning finds its application in autonomous vehicles and medical diagnoses. This is an increasingly important area of deep learning that aims to quantify the noise and uncertainty that is often present in real-world datasets.
Python implementation of various soccer/football analytics methods such as Poisson goals prediction, Shin method, machine learning prediction... This is a companion python module for octosport medium blog.
A library providing math and statistics operations for numbers of arbitrary size.
PHP implementation of statistical probability distributions: normal distribution, beta distribution, gamma distribution and more.
Pieces of code that have appeared on my blog.
A comprehensive bundle of utilities for the estimation of probability of informed trading models: original PIN in Easley and O'Hara (1992) and Easley et al. (1996); Multilayer PIN (MPIN) in Ersan (2016); Adjusted PIN (AdjPIN) in Duarte and Young (2009); and volume-synchronized PIN (VPIN) in Easley et al. (2011, 2012). Implementations of various …
Generate point arrays for Geometry Nodes using cubic grid, golden angle (Fermat's spiral), poisson disc sampling, or import points from data sources in CSV, NPY, and VF (Unity 3D volume field) formats.
Fast Poisson Random Numbers in pure Julia for scientific machine learning (SciML)
CP-APR Tensor Decomposition with PyTorch backend. pyCP_APR can perform non-negative Poisson Tensor Factorization on GPU, and includes an interface for anomaly detection using the extracted latent patterns.
Data Science Portfolio
Prediction of Premier league standings using Poisson distribution
Data Wrangling, Linear Models & other misc. Inferential Statistics.
In this work, we examine the resilience of two complex network types (Erdos Renyi, and Power-Law/Scale-free) to potential delivered attacks and random errors.
10 Days of Statistics Challenges at HackerRank
A MATLAB project which applies the central limit theorem on PDFs and CDFs of different probability distributions.
A collection of probability models applied to football
A Python library for working with and training Hidden Markov Models with Poisson emissions.
A comprehensive collection of R scripts focusing on Probability and Statistics. Includes foundational data manipulation, Exploratory Data Analysis (EDA), statistical visualization (histograms, boxplots), and implementation of various probability distributions like Binomial, Normal, and Poisson. Ideal for showcasing core statistical computing skills
A machining feature dataset called MFDataset, containing 33 subcategories features.
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