Search Results for "code visualization" - Page 4
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Showing 109 open source projects for "code visualization"
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Python Tutorials
Machine Learning Tutorials
...This includes foundational Python concepts, data processing with libraries like NumPy and pandas, threading and multiprocessing for concurrency, and practical use of libraries such as Matplotlib for data visualization. It also provides tutorials on machine learning frameworks and concepts, including TensorFlow, PyTorch, Keras, Scikit-Learn, and reinforcement learning techniques. Each section contains organized code and explanations designed to help learners understand the underlying mechanics of Python and common computational approaches. -
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Multi-Agent Emergence Environments
Environment generation code for the paper "Emergent Tool Use"
multi-agent-emergence-environments is an open source research environment framework developed by OpenAI for the study of emergent behaviors in multi-agent systems. It was designed for the experiments described in the paper and blog post “Emergent Tool Use from Multi-Agent Autocurricula”, which investigated how complex cooperative and competitive behaviors can evolve through self-play. The repository provides environment generation code that builds on the mujoco-worldgen package, enabling... -
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Tensorflow 2017 Tutorials
Tensorflow tutorial from basic to hard
...Beyond the basics, the project includes examples of convolutional neural networks, recurrent networks, autoencoders, reinforcement learning, generative adversarial networks, and transfer learning workflows. By pairing code examples with conceptual explanations, the tutorials make abstract machine learning ideas accessible and encourage experimentation with TensorBoard visualization and distributed training. -
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MMdnn
Tools to help users inter-operate among deep learning frameworks
...During the model conversion, we generate some code snippets to simplify later retraining or inference. We provide a model collection to help you find some popular models. We provide a model visualizer to display the network architecture more intuitively. We provide some guidelines to help you deploy DL models to another hardware platform. -
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repo2docker GitHub Action
A GitHub action to build data science environment images
Trigger repo2docker to build a Jupyter enabled Docker image from your GitHub repository and push this image to a Docker registry of your choice. This will automatically attempt to build an environment from configuration files found in your repository. Images generated by this action are automatically tagged with both latest and <SHA> corresponding to the relevant commit SHA on GitHub. Both tags are pushed to the Docker registry specified by the user. If an existing image with the latest tag... -
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StellarGraph
Machine Learning on Graphs
StellarGraph is a Python library for machine learning on graphs and networks. The StellarGraph library offers state-of-the-art algorithms for graph machine learning, making it easy to discover patterns and answer questions about graph-structured data. It can solve many machine learning tasks. Graph-structured data represent entities as nodes (or vertices) and relationships between them as edges (or links), and can include data associated with either as attributes. For example, a graph can... -
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Python Handout
Turn Python scripts into handouts with Markdown and figures
Handout is a lightweight library for embedding rich, interactive components such as exercises, charts, and interactive diagrams directly into static documents like Markdown, Jupyter notebooks, or static HTML pages, enabling authors to create more engaging technical handouts, tutorials, and interactive essays. It’s particularly aimed at educators, presenters, and researchers who want to make their written material come alive with runnable demonstrations and interactive problem sets without... -
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ChainerRL
ChainerRL is a deep reinforcement learning library
ChainerRL (this repository) is a deep reinforcement learning library that implements various state-of-the-art deep reinforcement algorithms in Python using Chainer, a flexible deep learning framework. PFRL is the PyTorch analog of ChainerRL. ChainerRL has a set of accompanying visualization tools in order to aid developers' ability to understand and debug their RL agents. With this visualization tool, the behavior of ChainerRL agents can be easily inspected from a browser UI. Environments... -
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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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captcha_break
Identification codes
This project will use Keras to build a deep convolutional neural network to identify the captcha verification code. It is recommended to use a graphics card to run the project. The following visualization codes are jupyter notebookall done in . If you want to write a python script, you can run it normally with a little modification. Of course, you can also remove these visualization codes. captcha is a library written in python to generate verification codes. ... -
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Django REST Pandas
Serves up Pandas dataframes via the Django REST Framework
Django REST Pandas (DRP) provides a simple way to generate and serve pandas DataFrames via the Django REST Framework. The resulting API can serve up CSV (and a number of other formats for consumption by a client-side visualization tool like d3.js. The design philosophy of DRP enforces a strict separation between data and presentation. This keeps the implementation simple, but also has the nice side effect of making it trivial to provide the source data for your visualizations. This capability can often be leveraged by sending users to the same URL that your visualization code uses internally to load the data. ... -
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PythonRobotics
Python sample codes and textbook for robotics algorithms
PythonRobotics is a Python code collection and textbook for learning robotics algorithms through readable examples. It covers practical topics such as localization, mapping, path planning, path tracking, control, SLAM, and autonomous navigation. The project is written to make each algorithm’s core idea easy to understand, rather than hiding the logic behind large frameworks. It keeps dependencies minimal so learners can focus on the math, implementation, and behavior of each robotics method.... -
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Easy-TensorFlow
Simple and comprehensive tutorials in TensorFlow
...In addition to the aforementioned points, the large community of TensorFlow enriches the developers with the answer to almost all the questions one may encounter. Furthermore, since most of the developers are using TensorFlow for code development, having hands-on on TensorFlow is a necessity these days. Tensorboard is a powerful visualization suite that is developed to track both the network topology and performance, making debugging even simpler. -
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GeoNotebook
A Jupyter notebook extension for geospatial visualization and analysis
GeoNotebook is an open-source extension to the Jupyter Notebook ecosystem that equips users with powerful geospatial visualization and analysis capabilities directly within the notebook interface. It integrates with GeoJS and other geospatial services to enable rich, interactive map rendering, layer control, and GIS data manipulation alongside traditional code and markdown cells in a Jupyter environment. Users can execute Python geospatial analysis and immediately visualize results on slippy web maps, allowing them to explore, annotate, and interpret large spatial datasets without leaving the notebook. ... -
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data-science-ipython-notebooks
Data science Python notebooks: Deep learning
...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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Python Data Science Tutorials
Common data analysis and machine learning tasks using python
Python Data Science Tutorials is a curated learning repository for common data analysis, machine learning, and natural language processing tasks in Python. It combines external tutorials, courses, reference guides, notebooks, articles, and selected code examples. The collection begins with Python fundamentals and then moves into scientific computing, statistics, NumPy, pandas, data exploration, and visualization. Its machine learning sections cover practical algorithms and libraries, including regression, classification, clustering, support vector machines, and computer vision resources. ... -
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plot.py
direct data plotting and evaluation
...The data treatment includes non-linear fitting, integration and differentiation, peak-finder and more. User python code can be executed in the integrated IPython console. -
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Deep Reinforcement Learning TensorFlow
TensorFlow implementation of Deep Reinforcement Learning papers
Deep Reinforcement Learning TensorFlow is a comprehensive TensorFlow codebase that implements several foundational deep reinforcement learning algorithms for educational and experimental use. The repository focuses on clarity and modularity so users can study how different RL approaches are built and compare their behavior across environments. It includes implementations of well-known algorithms such as Deep Q-Networks (DQN), policy gradients, and related variants, demonstrating how neural... -
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Construct2D
COmputational fluid dyNamics STRUctured grid CreaTor for 2D airfoils
Construct2D is a grid generator designed to create 2D grids for CFD computations on airfoils. The grids are generated in Plot3D format. The only required input file is the set of coordinates defining the airfoil geometry, using the same format as XFoil, the popular vortex-panel code for airfoil analysis. Construct2D can create grids with O topology (recommended for airfoils with a blunt trailing edge) or C topology (recommended for airfoils with a sharp trailing edge). Now available in... -
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Matplotlib tutorial
Matplotlib tutorial for beginner
...Because it is code-first, users can copy, modify, and run the examples on their own datasets, encouraging experimentation and deepening understanding. -
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RoboComp is a robotics framework providing a set of open-source, distributed, real-time robotic and artificial vision software components and the necessary tools to create and manage them.
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NanoCap
Carbon Fullerene and Capped Nanotube Generator
NanoCap is a generic application for the construction of low energy fullerene and capped nanotube structures. It provides an ideal tool to accompany the study of finite carbon molecules using computer simulation. The implementation involves a standalone application which includes a GUI and allows for dynamic visual inspection through 3D rendering. In addition, the NanoCap core libraries can be used in custom Python scripts that enabled the user to produce structures in bulk or to include the... -
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FortGrapher
InLine Plot with Fortran
This is a Fortran Module that merges the performance of the computation of the Fortran with the power of a Python Package called Matplotlib plot the data computed by your fortran code. It allows you to divide you data into groups of datafiles and each group is stored on its own directory. It allows you to create different types of plotting files such as, PNG file for each datafile and PDF and MPEG files for each group of datafiles. It works with FORMATTED and UNFORMATTED fortran... -
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pyscope
Software oscilloscope using Python and tkinter
Software oscilloscope using Python and tkinter. Supports multiple sources: socket, file, audio, USB. Displays data by samples, time or frequency. Scales the input automatically or manually. It has been renamed "pdatascope" to avoid a name-clash with Pyscope, a scoping package on PyPi. See https://sourceforge.net/p/pydatascope/ for the latest code. -
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PyCDep is a tool to analyze include dependencies between files in C and C++ programs. PyCDep itself is written in python. It dumps all the facts in a prolog database which can be queried. Visualization is possible by dumping graphviz (.dot) files.