Search Results for "bingo python code" - Page 5
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134 projects for "bingo python code" with 2 filters applied:
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IfSharp
F# for Jupyter Notebooks
F# for Jupyter Notebooks. This implements F# for Jupyter notebooks. View the Feature Notebook for some of the features that are included. There's a related project of .NET Interactive which was inspired by this one but a completely rethought approach with integrated package management, VS Code support, and variable sharing between languages. If you're moving to .NET Core support it's definitely worth checking out. -
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RecNN
Reinforced Recommendation toolkit built around pytorch 1.7
This is my school project. It focuses on Reinforcement Learning for personalized news recommendation. The main distinction is that it tries to solve online off-policy learning with dynamically generated item embeddings. I want to create a library with SOTA algorithms for reinforcement learning recommendation, providing the level of abstraction you like. -
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Climate Modeling Courseware
Interactive lecture notes and assignments in Jupyter notebook format
...The focus of the course is on the hands-on use of both simple and complex climate models to build an understanding of the processes that control the planetary energy budget. The course makes extensive use of Python code and the Jupyter notebook for reproducible, self-describing calculations and figures. This repository contains a collection of linked Jupyter notebooks with lecture notes, examples and assignments. All notebooks are self-describing. -
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pytorch-examples
Simple examples to introduce PyTorch
The pytorch-examples project is a collection of concise and practical examples demonstrating how to use PyTorch for machine learning and deep learning tasks. It focuses on clarity and minimalism, providing small, self-contained scripts that illustrate key concepts such as neural network training, optimization, and data handling. The examples cover a range of topics including supervised learning, generative models, and reinforcement learning, making it a valuable resource for both beginners... -
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data-science-ipython-notebooks
Data science Python notebooks: Deep learning
...Advanced sections touch on neural networks and distributed computing topics, helping you bridge from basics to production-adjacent workflows. The collection is suitable for self-paced study, quick reference, or as teaching materials in workshops. By combining narrative explanations with executable code, it shortens the path from theory to working prototypes. -
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CFD Python
Sequence of Jupyter notebooks featuring the 12 Steps to Navier-Stokes
CFD Python, a.k.a. the 12 steps to Navier-Stokes, is a practical module for learning the foundations of Computational Fluid Dynamics (CFD) by coding solutions to the basic partial differential equations that describe the physics of fluid flow. The module was part of a course taught by Prof. Lorena Barba between 2009 and 2013 in the Mechanical Engineering department at Boston University (Prof. Barba since moved to George Washington University). The module assumes only basic programming... -
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Autologging
Easier logging and tracing of Python functions and class methods.
Autologging eliminates boilerplate logging setup code and tracing code, and provides a means to separate application logging from program flow and data tracing. Autologging provides two decorators and a custom log level: "autologging.logged" decorates a class to create a __log member. By default, the logger is named for the class's containing module and name (e.g. "my.module.ClassName"). -
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Ponder
C++ reflection library with Lua binding, and JSON and XML
...For example, Ponder can be used to expose and edit objects' attributes in a graphical user interface. It can also be used to do automatic binding of C++ classes to script languages such as Python or Lua. Another possible application would be the serialization of objects to XML, text or binary formats. Or you can even combine all these examples to provide a powerful and consistent interface for manipulating your objects outside C++ code. -
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Python/xarray tutorial
Python/xarray tutorial for GEOS-Chem users
If the page is loaded successfully, you should see a Jupyter notebook interface. Then, click on the first notebook to get started. Jupyter combines Python code, execution results, plots, custom texts, and even Latex formulas in a single page. Besides using the Jupyter program, you can also view the static notebook on GitHub (e.g the first notebook). Python is free & open-source so can be easily installed on any machines. To best way to get the scientific Python environment is using the Conda management system. ... -
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cnn-text-classification-tf
Convolutional Neural Network for Text Classification in Tensorflow
The cnn-text-classification-tf repository by Denny Britz is a well-known educational implementation of convolutional neural networks for text classification using TensorFlow, aimed at helping developers and researchers understand how CNNs can be applied to natural language processing tasks. Based loosely on Kim’s influential paper on CNNs for sentence classification, this codebase demonstrates how to preprocess text data, convert words into learned embeddings, and apply multiple convolution... -
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Compare GAN
Compare GAN code
compare_gan is a research codebase that standardizes how Generative Adversarial Networks are trained and evaluated so results are comparable across papers and datasets. It offers reference implementations for popular GAN architectures and losses, plus a consistent training harness to remove confounding differences in optimization or preprocessing. The library’s evaluation suite includes widely used metrics and diagnostics that quantify sample quality, diversity, and mode coverage. With... -
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Zhao
A compilation of "The Princely Party Relationship Network"
zhao is a repository that consolidates research, data, and insights related to Zhao, which is likely an individual’s research collection, notes, or curated resources on deep learning, AI, or computational topics (name and content context suggest specialized study). The project may include code examples, experiment results, references to academic papers, mathematical notes, and supporting scripts to explore specific ML methods, benchmarks, or theoretical findings. Because it aggregates... -
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Assorted projects. General-purpose libraries for Python, C++, Scala, bash, and others. Meta-programming tools. System utilities. UI components. Web APIs. Configuration files. Benchmarks. Programming competition entries. And much more.
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Pyrlang
Erlang node implemented in Python 3.5+ (Asyncio-based)
This is a drop-in Erlang node implementation in Python 3, implementing a network Erlang node protocol. It was designed to allow interoperation between existing Python projects and BEAM languages: Erlang, Elixir, Gleam, Luaerl, LFE, Clojerl, and such. With just a few lines of startup code your Python program becomes an Erlang network node, participating in the Erlang cluster. -
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Flasky
Companion code to my O'Reilly book "Flask Web Development"
Flasky is a comprehensive example web application built with the Flask microframework that demonstrates best practices for developing real-world Python web applications, covering everything from project structure and configuration to database models, authentication, and deployment. It serves as both a tutorial and sample codebase that walks developers through building a full-featured web application, including user registration and login, role-based permissions, user profiles, and content... -
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Python in neuroscience
Collection of tutorials about methods of computational neuroscience
"Python in neuroscience" is a collection of collaboratively edited tutorials on computational neuroscience methods using Python language. Each tutorial is presented as a literate programming tutorial mixing text, code, and figures. The tutorials offer an introduction to basic methods of computational neuroscience and scientific programming in Python. -
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Icon Font to PNG
Python script (and library) for exporting icons from icon fonts
...You can use IconFont (and IconFontDownloader for that matter) directly inside your Python project. There's no proper documentation as of now, but the code is commented and should be pretty straightforward to use. -
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Projects-Solutions
Links to others' solutions to Projects
...It is effectively a community-driven gallery of implementations of the tasks defined in the “Projects” list, allowing learners to compare their solutions, study others’ code, and improve their approach. The repository aggregates links and resources rather than necessarily hosting all code directly; it serves as an index. The README makes clear that the goal is to build a repository of implementations across languages, showing that the same problem can be solved in Python, Java, Go, JavaScript, C++, etc. ... -
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PyPattyrn
A simple library for implementing common design patterns
PyPattyrn is a Python package aiming to make it easier and faster to implement design patterns into your own projects. Design patterns by nature cannot be directly translated into code as they are just a description of how to solve a particular problem. However, many of the common design patterns have boilerplate code that is common throughout all implementations of the pattern. -
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ffnet is a fast and easy-to-use feed-forward neural network training solution for python. Many nice features are implemented: arbitrary network connectivity, automatic data normalization, very efficient training tools, network export to fortran code. Now ffnet has also a GUI called ffnetui.
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ArmaNpy is a set of SWIG interface files which allows for generating Python bindings to C++ code which uses the Armadillo matrix library.
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pyhrol
Bridge between C++ and Python
Dynamic C++ library for simplification of binding C++ projects to Python. Supports argument overloading. Automatically generates help on method signatures, including default values. Automatically generates list of named parameters. Supports primary Python protocols: Number, Sequence, Mapping, Iterator Protocol. Includes more than 40 code examples. CMake driven. Supports Python 2.x. Does not support Python 3.x (planned). -
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musicinformationretrieval.com
Instructional notebooks on music information retrieval
musicinformationretrieval.com is a collection of instructional materials for music information retrieval (MIR). These materials contain a mix of casual conversation, technical discussion, and Python code. These pages, including the one you're reading, are authored using Colab notebooks. -
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Py4J enables Python programs to dynamically access arbitrary Java objects. Methods are called as if the Java objects resided in the Python virtual machine. There is no code to generate and no interface to implement for shared objects on both sides.
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ProximityForest
Efficient Approximate Nearest Neighbors for General Metric Spaces
A proximity forest is a data structure that allows for efficient computation of approximate nearest neighbors of arbitrary data elements in a metric space. See: O'Hara and Draper, "Are You Using the Right Approximate Nearest Neighbor Algorithm?", WACV 2013 (best student paper award). One application of a ProximityForest is given in the following CVPR publication: Stephen O'Hara and Bruce A. Draper, "Scalable Action Recognition with a Subspace Forest," IEEE Conference on Computer...
