Search Results for "data modeling"
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Showing 27 open source projects for "data modeling"
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Perfect Roadmap To Learn Data Science
Basic To Intermediate Python data science guide
...What makes it particularly valuable is its holistic nature: rather than focusing only on modeling or theory, it also addresses the broader lifecycle of data-science work, data ingestion, cleaning, EDA, feature engineering, model building, validation, deployment, etc. -
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Book5_Essentials-Probability-Statistics
The book 5 of statistics in simplicity
Book5_Essentials-of-Probability-and-Statistics is a Visualize-ML educational volume that introduces the statistical and probabilistic concepts underpinning modern data analysis and machine learning. The repository explains topics such as distributions, sampling, inference, and uncertainty using visual demonstrations and intuitive narratives. Its teaching philosophy prioritizes conceptual clarity over heavy formalism, making statistical thinking more approachable for beginners. The material connects probability theory directly to real analytical workflows, helping learners understand how statistics supports predictive modeling. ... -
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Computational Thinking
Introduction to computational thinking with Julia
Computational Thinking is an open source MIT course repository that teaches computational problem-solving through the Julia programming language. The course integrates mathematics, computing, and real-world applications into a unified curriculum, making it suitable for students across science, engineering, and data-driven fields. It emphasizes learning how to translate problems into computational terms and developing algorithms and models to analyze them effectively. Using Julia, the course... -
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Hello SQL
Spanish-language course repository that teaches fundamentals of SQL
...The materials emphasize real-world query writing, schema design basics, and the mental model behind SELECT, JOIN, GROUP BY, and subqueries. Learners progress from setup and connection to hands-on exercises that build confidence with CRUD operations and data modeling. The repository’s structure favors incremental learning, with clear folders, references, and exercises you can run locally. It targets absolute beginners as well as developers from other stacks who want a clean, project-based path into SQL. -
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MathMod
MathMod is a mathematical modeling software
MathMod is a portable interactive plotting and graphing program for Windows, Linux, MacOSX and many other platforms. MathMod allows to plot 3D mathematical surfaces, described by implicit or parametric equations, and offers a very large database of model samples that can be generated with it. It's Free and Open Source. Change-log for MathMod-13.0 (15/11/2025) 1) Scripts generator to add thickness to iso/parametric surfaces 2) Undo/Redo commands for navigating through previous... -
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General Knowledge Machine Project
Intellect Modeling Kit: assisting research, diagnostics, consulting
...All knowledge is far beyond power of any person. The only way to apply knowledge is to build machines able to present it human way but not limited by volume. Intellect Modeling Kit (IMK) is intended to build knowledge machines (KM) assisting experts on the steps of activity: * Observation; * Producing propositions based on knowledge; * Elimination of impossible propositions; * Selection and verification of the most appropriate propositions; * Memorizing - new knowledge item creation; * Abstraction – building objects representing typical signs of similar objects groups, data mining. ... -
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Bayesian Methods for Hackers
An introduction to Bayesian methods + probabilistic programming
...It is written from a computation-first perspective, prioritizing intuition, examples, and executable notebooks over heavy mathematical formalism. The project introduces readers to uncertainty, Bayesian modeling, MCMC, priors, posteriors, and real-world probabilistic reasoning. It includes notebook-based chapters that let learners run and modify examples directly. The material is especially useful for programmers, data scientists, and technically curious readers who want to learn Bayesian methods through code. It remains a widely referenced entry point for making Bayesian statistics feel practical and approachable. -
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DeepMind Educational Resources
DeepMind's repo of educational notebooks for learning AI and research
...The repository provides hands-on, beginner-friendly resources that introduce essential AI concepts through Google Colab notebooks, combining intuitive explanations with executable code. The tutorials cover a broad range of topics—from foundational Python programming and data handling to supervised, unsupervised, and reinforcement learning, as well as graph neural networks and scientific reasoning. Specialized notebooks also explore creative AI applications, language modeling, generative models, and protein folding. Each tutorial is designed to be standalone and adaptable for self-study, classroom teaching, or use at summer schools and community workshops. -
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Data Analysis for the Life Sciences
Rmd source files for the HarvardX series PH525x
This repository holds the R Markdown (.Rmd) source files for the PH525x / HarvardX course series (Data Analysis for the Life Sciences / Genomics) managed by GenomicsClass. It functions as the canonical source for course lab exercises, lecture modules, and reading materials in reproducible format. Students and learners use these R Markdown files to follow along, knit notebooks, run code samples, and complete the lab-based assignments. The repo is licensed under MIT, allowing reuse and... -
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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. -
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Stats With Julia Book
Collection of runnable Julia code examples for a statistics book
...Readers can explore how Julia supports statistical modeling, simulation, and computational methods in data science workflows. The included initialization script simplifies package setup, ensuring that learners can focus on running and modifying the code examples. This project bridges the gap between textbook learning and hands-on coding, making it a valuable educational tool for students, researchers, and practitioners. -
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covid19model
Code for modelling estimated deaths and cases for COVID19
Code for modeling estimated deaths and infections for COVID-19 from "Estimating the effects of non-pharmaceutical interventions on COVID-19 in Europe", Flaxman, Mishra, Gandy et al, Nature, 2020, the published version of our original Report 13. This is the release related to our Tiers paper, where we use the latent factor model to estimate the effectiveness of tiers systems in England. Peer-reviewed version is to be out soon. All other code is still the same for previous releases. The code... -
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Quantitative-Notebooks
Educational notebooks on quantitative finance, algorithmic trading
...Because quantitative analysis often requires visualization, statistics, and time series processing, these notebooks also serve as templates for real financial research and strategy prototyping. Users can adapt the examples to their own data sources, financial instruments, and modeling techniques. -
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swirl
Learn R, in R
swirl is an R package that allows interactive, in-R learning of statistics, data science, R programming etc. The idea is that you load swirl in R, and it presents you with lessons (within R’s console or RStudio) that ask you to type commands, check results, and progress through tutorial material—without leaving the R environment. It is used for teaching R, especially for beginners, as well as for self-paced learning of packages, data manipulation, visualization, etc. Lessons and content are... -
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Scikit-learn Tutorial
An introductory tutorial for scikit-learn
Scikit-learn Tutorial contains the materials for Jake VanderPlas’s introductory scikit-learn tutorial, originally used at major Python conferences. It provides a collection of notebooks that walk attendees from basic machine-learning concepts into practical modeling using the scikit-learn library. The tutorial covers data preparation, model fitting, evaluation, and common algorithms such as classification, regression, clustering, and dimensionality reduction. It is designed for people who already have a working Python environment and some familiarity with NumPy, SciPy, and Matplotlib. The repository specifies a clear list of dependencies so that participants can reproduce the environment used in the tutorial, and many downstream forks keep the content updated for newer versions of scikit-learn. ... -
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That project aims at providing a clean API, and the corresponding C++ implementation, for choosing one item among a set of travel solutions, given demand-related characteristics (e.g., Willingness-To-Pay, preferred airline, preferred cabin, etc.).
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cvsba
OpenCV wrapper for sba library
cvsba is an OpenCV wrapper for the well-known Sparse Bundle Adjustment library (sba) by M. Lourakis. The main features are: - Based on sba-1.6, one of the most popular and robust bundle adjustment implementation, which is extensively used and tested by the community - sba installation is not needed since it is included in cvsba - New CMake structure which makes the library compilation, installation and linkage easier - Similar interface than Bundle Adjustment implementation on... -
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itermd
Software tools for applications of simulations by iterations.
For simulations or modeling studies of regulations, Automation or various phenomena, with parameters that may be random, interdependent variables without simple rules, etc.. It can also be used to study mathematical curves remarkable how 'pragmatic'. The claim of these tools is to facilitate the programming of simulations by providing routines to quickly generate: -display windows and input parameters -help to display the variation in the data as graphs -management of iterations Goal for the user: quickly programme his simulation. ... -
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Firefly UML
A free, easy-to-use and user-friendly Java-based UML editor.
Firefly UML is a 100% pure Java application designed to create and edit UML conform diagrams. With class diagrams, sequence and instance diagrams, Firefly UML provides a solid selection from the vast range of existing UML diagram types. Firefly UML is really easy to learn as it provides you multiple ways of access to the same function - be it mouse action, hotkey, context menu or toolbar icon. And the best thing is: once you have learned how to handle one type of diagram, you also have... -
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BPMN extension for Cloud computing
java project for modifying jBPM models into cloud aware models
Program based on created BPMN 2.0 Cloud extension. It reads a model *.bpmn, which was created using jBPM BPMN 2.0 modeling tool. Then user is able to define a sensitivity of data elements. After that an Ontology is created and filled in with model elements. Special logical rules process the data. User is able to additionally define the security level. The resulting model is created and can be opened in the jBPM. -
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GeoSolid3D produces 3D geologic solid models, incorporated into the aquifer and confining units of the USGS ground water models, Modflow and Sutra. Uses GIS data of DEMs, geologic maps, and maps of river, watershed, recharge, and aquifer parameters.
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A java library for the processing and analysis of natural language texts and other sequential data. The focus is on unsupervised modeling with simple, statistical methods as well as implementations of more complex algorithms.
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Main Phase Modeling, MPM, is a implementation of a 2D staggered grid solution of the elastic waveequation, using a moving zone. This enables both efficient modeling of seismic wide angle data, and modeling of selected propagating phases.
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Reason is rare. The reasoning behind day to day decisions and important issues are often unknown, unadmitted or misunderstood.Argumentative allows you to express an argument’s structure in a visual form which is simpler to understand.
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This open-source project aims at creation of a OpenGL 3D stereoscopic algorithms folded as plug-ins into popular 3D modeling and game engine tools, such as Maya, Blender, OGRE, and others.
