Search Results for "probability"
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Showing 24 open source projects for "probability"
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Book5_Essentials-Probability-Statistics
The book 5 of statistics in simplicity
...The material connects probability theory directly to real analytical workflows, helping learners understand how statistics supports predictive modeling. Like the other books in the series, it blends mathematical explanation with Python-based experimentation. Overall, the project provides a practical statistical foundation for students advancing into AI and data science. -
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ThinkStats2
Text and supporting code for Think Stats, 2nd Edition
ThinkStats2 is the code and text companion for the second edition of Think Stats, an introduction to statistics and data science for Python programmers. It teaches probability and statistical reasoning through short programs, experiments, and analysis of real datasets. The material emphasizes exploratory methods that help readers ask and answer practical questions with data. Case studies draw from public sources, including health-related datasets, to connect abstract concepts with realistic analysis. ... -
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Statistics101 - Resampling Statistics
Use simulation to perform statistical analyses.
Statistics101 is an Integrated Development Environment (IDE) that uses a simple, powerful language called “Resampling Stats” to develop Monte Carlo programs to analyze and solve statistical problems. The original Resampling Stats language and computer program were developed by Dr. Julian Simon (https://www.juliansimon.com/) and Peter Bruce (https://www.scientificamerican.com/author/peter-bruce/) as a new way to teach Statistics to social science students. Of course, social science students... -
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BEDS - Bed Evaluation & Design System
A system for designing and evaluating patient flow in hospitals.
...Patients have a single preference for hospitalization in a specific ward. If the preferred ward is fully occupied on arrival, the patient is relocated to an alternative ward with a known probability. Several scientific studies have shown that this simple setup is an adequate approximation for describing the occupancy in inpatient wards. -
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Statistics for Data Scientists
"Statistics for Data Scientists: 50 Essential Concepts"
The “statistics-for-data-scientists” repository is a pedagogical resource designed to bridge rigorous statistics theory and practical data science workflows. The code and materials are intended to help data scientists and analysts grasp statistical principles (e.g. inference, regressions, hypothesis testing, probability, confidence intervals) in contexts relevant to real data analysis tasks. The repository includes Jupyter notebooks, R scripts, worked examples, and possibly problem sets that illustrate how statistical methods are applied to real datasets. It aims to demystify the bridge between textbook statistics and empirical modeling by walking through assumption checking, visualization, interpreting outputs, and pitfalls of misuse. ... -
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stat-cookbook
The probability and statistics cookbook
A compact “Probability and Statistics Cookbook” offering concise mathematical recipes for key statistical concepts—expectation, variance, distributions and inequalities—packaged as LaTeX and R-based executable documents. -
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Stats With Julia Book
Collection of runnable Julia code examples for a statistics book
StatsWithJuliaBook is the companion code repository for the book Statistics with Julia: Fundamentals for Data Science, Machine Learning and Artificial Intelligence. It contains over 200 code blocks that correspond to the book’s ten chapters and three appendices, covering topics from probability theory and data summarization to regression analysis, hypothesis testing, and machine learning basics. The repository is designed for Julia users and provides ready-to-run examples that reinforce theoretical concepts with practical implementation. Readers can explore how Julia supports statistical modeling, simulation, and computational methods in data science workflows. ... -
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Think Bayes
Code repository for Think Bayes
...Instead of heavy focus on continuous mathematics or calculus, the book emphasizes learning Bayesian inference by writing Python programs. The project includes code examples, scripts, and environments that correspond to the chapters of the book. Learners can run the code, experiment with probability distributions, compute posterior probabilities, and understand Bayesian updating via simulation and algorithmic methods. The book and code encourage thinking in terms of discrete approximations (sums over distributions) rather than continuous integrals, making it more accessible to many programmers. Over time, the repository has been updated (including a second edition version) to reflect improved practices, corrections, and modern Python tooling. -
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DeepLearning
Deep Learning (Flower Book) mathematical derivation
...The full name is also called the Deep Learning AI Bible (Deep Learning) . It is edited by three world-renowned experts, Ian Goodfellow, Yoshua Bengio, and Aaron Courville. Includes linear algebra, probability theory, information theory, numerical optimization, and related content in machine learning. At the same time, it also introduces deep learning techniques used by practitioners in the industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling and practical methods, and investigates topics such as natural language processing, Applications in speech recognition, computer vision, online recommender systems, bioinformatics, and video games. ... -
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jieba
Stuttering Chinese word segmentation
"Jaba" Chinese word segmentation, do the best Python Chinese word segmentation component. Four word segmentation modes are supported. Precise mode, which tries to cut the sentence most precisely, suitable for text analysis. Full mode, scans all the words that can be formed into words in the sentence, the speed is very fast, but the ambiguity cannot be resolved. The search engine mode, on the basis of the precise mode, divides the long words again to improve the recall rate, which is suitable... -
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PRMLT
Matlab code of machine learning algorithms in book PRML
...Many tricks for speeding up Matlab code are applied (e.g. vectorization, matrix factorization, etc.). Usually, functions in this package are orders faster than Matlab builtin ones (e.g. kmeans). Many tricks for numerical stability are applied, such as computing probability in logrithm domain, square root matrix update to enforce matrix symmetry. -
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MandelbrotExplorer
A program to calculate and represent the Mandelbrot set
This project is a C++ program to calculate and represent graphically the Mandelbrot fractal set, and/or the corresponding Julia sets, according to the seed Z0 given by the user as input. The user disposes of a graphical interface to control the program and modify conveniently some parameters, like the XY-scales, the XY map area, the Julia seed for the complex series iteration of Z(n+1)=Z(n)^2+a, being Z(0)=(X0,Y0) the seed, and "a in XY" the points to be calculated. The user can... -
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Cambridge Rocketry Simulator
Simulate high power rocket flights with splash down plots
...Parachute descent is also simulated. 3D flight trajectories are produced as well as detailed tabular flight data. Running in Monte Carlo mode allows generates multiple possible flight paths and splash down plots, indicating the probability of landing in an area. Peer-reviewed publication in the Journal of Open Research Software (JORS) http://doi.org/10.5334/jors.137 "Cambridge Rocketry Simulator – A Stochastic Six-Degrees-of-Freedom Rocket Flight Simulator" -
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The Bible Code
Searching skip code ciphers in Torah and other texts.
Searching skip code ciphers in Torah and other texts. -
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Myrtle
A simple programmable spreadsheet for learning statistics.
...It provides the standard spreadsheet functionality one would expect like multiple tabbed sheets, relative and absolute row and column referencing in formulas, and a large catalog of built-in functions. Functions specific to logic and computer science, mathematics, probability, and statistics are available. Student's can easily create, customize, and update plots and graphical summaries of their analyses. Myrtle offers a unique bookmarking facility which allows students to create and reuse named references to their favorite cell ranges. This can help students focus attention on the important relationships among particular rows or columns of data. ... -
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Binomial Distribution Calculator
A simple to use Binomial Distribution Calculator.
A simple to use binomial distribution calculator: Just enter the sufficient data like number of trials, probability and number of successes. You can display the calculated data in a table or even graphically. Simultaneously, this application computes the expected value and the standard deviation. To use this app you need to have .NET Framework 4 installed. Contact me: lambdapew-dev@yahoo.de -
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Plots Binomial and Poisson distributions based on different values of p and n to visually express, how much those distributions are "close"
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Monopoly Probability Calculator calculates the probability of each field in the game Monopoly and displays it in different colors. It gives you a tactical advantage against your opponents. There will be a benchmark mode in the future.
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The purpose of this program is to plot the waveforms of the hydrogen wave function. The program has 4 option's. First, plotting the radial function, second, plotting the radial probability, third, 2d wave function,last, 3d wave function.
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GradeSignifier provides statistical significance testing for item response data. In a few clicks you can: convert raw test data into scores, determine if the scores of two groups differ significantly, make cumulative probability charts, and more.
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A web-based prediction market (Idea Futures) system. In prediction markets, the commodities traded are claims about future events; the market price gives a consensus probability about the event's likelihood of coming true.
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This is a prolog-like programming language based on the fuzzy logic. It includes the class-libraries for fuzzy logic, probability theory and method of resolution, all made in C++. Java releases possible in the future.
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Java/XML toolkit for research using Bayesian networks and other graphical models of probability (exact and approximate inference, structure learning, etc.)
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