94 projects for "python games code" with 2 filters applied:

  • AestheticsPro Medical Spa Software Icon
    AestheticsPro Medical Spa Software

    Our new software release will dramatically improve your medspa business performance while enhancing the customer experience

    AestheticsPro is the most complete Aesthetics Software on the market today. HIPAA Cloud Compliant with electronic charting, integrated POS, targeted marketing and results driven reporting; AestheticsPro delivers the tools you need to manage your medical spa business. It is our mission To Provide an All-in-One Cutting Edge Software to the Aesthetics Industry.
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  • Award-Winning Medical Office Software Designed for Your Specialty Icon
    Award-Winning Medical Office Software Designed for Your Specialty

    Succeed and scale your practice with cloud-based, data-backed, AI-powered healthcare software.

    RXNT is an ambulatory healthcare technology pioneer that empowers medical practices and healthcare organizations to succeed and scale through innovative, data-backed, AI-powered software.
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  • 1
    minimalRL-pytorch

    minimalRL-pytorch

    Implementations of basic RL algorithms with minimal lines of codes

    minimalRL is a lightweight reinforcement learning repository that implements several classic algorithms using minimal PyTorch code. The project is designed primarily as an educational resource that demonstrates how reinforcement learning algorithms work internally without the complexity of large frameworks. Each algorithm implementation is contained within a single file and typically ranges from about 100 to 150 lines of code, making it easy for learners to inspect the entire implementation...
    Downloads: 0 This Week
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  • 2
    picoGPT

    picoGPT

    An unnecessarily tiny implementation of GPT-2 in NumPy

    picoGPT is a minimal implementation of the GPT-2 language model designed to demonstrate how transformer-based language models work at a conceptual level. The repository focuses on educational clarity rather than production performance, implementing the core components of the GPT architecture in a concise and readable way. It allows users to understand how tokenization, transformer layers, attention mechanisms, and autoregressive text generation operate in modern large language models. The...
    Downloads: 0 This Week
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  • 3
    Mars Framework

    Mars Framework

    Mars is a tensor-based unified framework for large-scale data

    Mars is a distributed computing framework designed to scale scientific computing and data science workloads across large clusters while preserving the familiar programming interfaces of common Python libraries. The project provides a tensor-based execution model that extends the capabilities of tools such as NumPy, pandas, and scikit-learn so that large datasets can be processed in parallel without rewriting code for distributed environments. Its architecture automatically divides large computational tasks into smaller chunks that can be executed across multiple nodes in a cluster, allowing complex analytics, machine learning workflows, and data transformations to run efficiently at scale. ...
    Downloads: 5 This Week
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  • 4
    UnionML

    UnionML

    Build and deploy machine learning microservices

    ...Data science, ML engineering, and MLOps practitioners can all gather around UnionML apps as a way of defining a single source of truth about your ML system’s behavior. This helps you maintain consistent code across your ML stack, from training to prediction logic.
    Downloads: 0 This Week
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  • Skillfully - The future of skills based hiring Icon
    Skillfully - The future of skills based hiring

    Realistic Workplace Simulations that Show Applicant Skills in Action

    Skillfully transforms hiring through AI-powered skill simulations that show you how candidates actually perform before you hire them. Our platform helps companies cut through AI-generated resumes and rehearsed interviews by validating real capabilities in action. Through dynamic job specific simulations and skill-based assessments, companies like Bloomberg and McKinsey have cut screening time by 50% while dramatically improving hire quality.
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  • 5
    d2l-zh

    d2l-zh

    Chinese-language edition of Dive into Deep Learning

    d2l‑zh is the Chinese-language edition of Dive into Deep Learning, an interactive, open‑source deep learning textbook that combines code, math, and explanatory text. It features runnable Jupyter notebooks compatible with multiple frameworks (e.g., PyTorch, MXNet, TensorFlow), comprehensive theoretical analysis, and exercises. Widely adopted in over 70 countries and used by more than 500 universities for teaching deep learning.
    Downloads: 0 This Week
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  • 6
    Python ML Jupyter Notebooks

    Python ML Jupyter Notebooks

    Practice and tutorial-style notebooks

    Python ML Jupyter Notebooks is an educational repository that demonstrates how to implement machine learning algorithms and data science workflows using Python. The project provides numerous examples and tutorials covering classical machine learning techniques such as regression, classification, clustering, and dimensionality reduction.
    Downloads: 0 This Week
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  • 7
    learn-machine-learning-in-two-months

    learn-machine-learning-in-two-months

    Essential Knowledge for learning Machine Learning in two months

    ...Many sections include notebooks and code examples that demonstrate how algorithms are implemented and trained using modern machine learning frameworks.
    Downloads: 0 This Week
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  • 8
    DialoGPT

    DialoGPT

    Large-scale pretraining for dialogue

    DialoGPT is an open-source conversational language model developed by Microsoft Research for generating natural dialogue responses using large-scale transformer architectures. The system is built on the GPT-2 architecture and is designed specifically for multi-turn conversation tasks, enabling machines to produce coherent responses during interactive dialogue. The model was trained on a massive dataset of approximately 147 million conversational exchanges extracted from Reddit discussion...
    Downloads: 0 This Week
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  • 9
    Python Machine Learning 3rd Ed.

    Python Machine Learning 3rd Ed.

    The "Python Machine Learning (3rd edition)" book code repository

    Python Machine Learning 3rd Ed. repository contains the complete source code that accompanies the book Python Machine Learning by Sebastian Raschka and collaborators. The project provides implementations of machine learning algorithms and data science workflows described in the book, enabling readers to experiment with real code while studying theoretical concepts.
    Downloads: 0 This Week
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  • The Industry Leading Platform for eCommerce Enablement and Analytics Icon
    The Industry Leading Platform for eCommerce Enablement and Analytics

    With MikMak Insights, brands gain real-time eCommerce analytics on the channels, campaigns, creative, and audiences that drive conversions.

    MikMak’s Where to Buy Shoppable Solutions help multichannel brands drive sales, grow market share, and increase profitability while reducing costs across categories such as CPG, Grocery, Alcohol, Beauty, Personal Care, Pet Care, Home Care, Consumer Electronics, Home Appliances, Toys, and more.
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  • 10
    ISLR-python

    ISLR-python

    An Introduction to Statistical Learning

    ...The datasets used in the book are also included so that users can run experiments directly within the provided notebooks. By translating the statistical learning material into Python code, the repository makes the book’s concepts accessible to a wider community of Python users.
    Downloads: 1 This Week
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  • 11
    Pattern Recognition and Machine Learning

    Pattern Recognition and Machine Learning

    Repository of notes, code and notebooks in Python

    Pattern Recognition and Machine Learning is an open-source repository that provides Python implementations and interactive notebooks for algorithms presented in the book Pattern Recognition and Machine Learning by Christopher Bishop. The project recreates many of the mathematical concepts and diagrams from the book using executable Jupyter notebooks, allowing readers to experiment directly with the algorithms described in the text.
    Downloads: 0 This Week
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  • 12
    Machine Learning Glossary

    Machine Learning Glossary

    Machine learning glossary

    Machine Learning Glossary is an open educational project that provides clear explanations of machine learning terminology and concepts through visual diagrams and concise definitions. The goal of the repository is to make machine learning topics easier to understand by presenting definitions alongside examples, visual illustrations, and references for further learning. It covers a wide range of topics including neural networks, regression models, optimization techniques, loss functions, and...
    Downloads: 0 This Week
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  • 13
    Talking Head Anime from a Single Image

    Talking Head Anime from a Single Image

    Demo for the "Talking Head Anime from a Single Image"

    Talking Head Anime from a Single Image is a machine learning project that demonstrates how neural networks can animate anime characters using only a single input image. The system generates animated facial expressions and movements by applying pose transformations to a static image of an anime character. The underlying model uses deep learning techniques to predict how different facial features and body parts should move based on pose parameters or input signals. This allows the software to...
    Downloads: 1 This Week
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  • 14
    MuZero General

    MuZero General

    A commented and documented implementation of MuZero

    muzero-general is an open-source implementation of the MuZero reinforcement learning algorithm introduced by DeepMind. MuZero is a model-based reinforcement learning method that combines neural networks with Monte Carlo Tree Search to learn decision-making policies without requiring explicit knowledge of the environment’s dynamics. The repository provides a well-documented and commented implementation designed primarily for educational purposes. It allows researchers and developers to train...
    Downloads: 0 This Week
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  • 15
    CodeSearchNet

    CodeSearchNet

    Datasets, tools, and benchmarks for representation learning of code

    ...These pairs allow machine learning models to learn relationships between natural language descriptions and programming code. The dataset currently covers several widely used programming languages, including Python, JavaScript, Ruby, Go, Java, and PHP. In addition to the dataset itself, the repository includes baseline models, evaluation tools, and instructions for building code retrieval systems that can map user queries to relevant code snippets.
    Downloads: 2 This Week
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  • 16
    AI Platform Training and Prediction
    AI Platform Training and Prediction is a collection of machine learning example projects that demonstrate how to train, deploy, and serve models using Google Cloud AI Platform and related services. It includes a wide variety of implementations across frameworks such as TensorFlow, PyTorch, scikit-learn, and XGBoost, allowing developers to explore different approaches to building ML solutions. The repository covers the full machine learning lifecycle, including data preprocessing, model...
    Downloads: 0 This Week
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  • 17
    Machine Learning Financial Laboratory

    Machine Learning Financial Laboratory

    MlFinLab helps portfolio managers and traders

    ...The library also includes tools for constructing specialized financial data structures, generating predictive features, and evaluating trading strategies through backtesting. Its architecture emphasizes reproducibility, robust testing, and well-documented code so that researchers and practitioners can reliably experiment with financial machine learning models.
    Downloads: 0 This Week
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  • 18
    scikit-learn tips

    scikit-learn tips

    50 scikit-learn tips

    ...Many tips are accompanied by Jupyter notebooks that allow users to explore the code interactively and understand how the techniques work in practice.
    Downloads: 0 This Week
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  • 19
    Machine Learning & Deep Learning

    Machine Learning & Deep Learning

    machine learning and deep learning tutorials, articles

    Machine Learning & Deep Learning Tutorials is an open-source repository that provides practical tutorials demonstrating how to implement machine learning and deep learning models using popular frameworks such as TensorFlow and PyTorch. The project focuses on helping learners understand machine learning through hands-on coding examples rather than purely theoretical explanations. Each tutorial walks through the process of building and training models for tasks such as image classification,...
    Downloads: 0 This Week
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  • 20
    Machine-Learning

    Machine-Learning

    kNN, decision tree, Bayesian, logistic regression, SVM

    Machine-Learning is a repository focused on practical machine learning implementations in Python, covering classic algorithms like k-Nearest Neighbors, decision trees, naive Bayes, logistic regression, support vector machines, linear and tree-based regressions, and likely corresponding code examples and documentation. It targets learners or practitioners who want to understand and implement ML algorithms from scratch or via standard libraries, gaining hands-on experience rather than relying solely on black-box frameworks. ...
    Downloads: 0 This Week
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  • 21
    tensorflow_template_application

    tensorflow_template_application

    TensorFlow template application for deep learning

    tensorflow_template_application is a template project that demonstrates how to structure scalable applications built with TensorFlow. The repository provides a standardized architecture that helps developers organize machine learning code into clear components such as data processing, model training, evaluation, and deployment. Instead of focusing on a specific algorithm, the project emphasizes software engineering practices that make machine learning systems easier to maintain and extend....
    Downloads: 0 This Week
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  • 22
    TensorFlow 2.0 Tutorials

    TensorFlow 2.0 Tutorials

    TensorFlow 2.x version's Tutorials and Examples

    TensorFlow 2.0 Tutorials is an open-source educational repository that provides practical examples and walkthroughs for learning deep learning using the TensorFlow 2.x framework. The repository contains a large set of hands-on tutorials that demonstrate how to build neural networks and machine learning systems with modern TensorFlow APIs. These examples cover a wide range of topics including convolutional neural networks, recurrent neural networks, generative adversarial networks,...
    Downloads: 0 This Week
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  • 23
    Knock Knock

    Knock Knock

    Get notified when your training ends

    ...The goal of the project is to allow developers to monitor experiments remotely without needing to stay connected to the training environment. By adding only a few lines of code, the library can wrap around a training function and report execution status.
    Downloads: 0 This Week
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  • 24
    python-is-cool

    python-is-cool

    Cool Python features for machine learning

    python-is-cool is an educational repository created by AI researcher Chip Huyen that explores lesser-known features and powerful capabilities of the Python programming language. The project serves as a curated guide to Python techniques that many developers may overlook or hesitate to use due to unfamiliarity. It demonstrates practical language features, idiomatic programming patterns, and useful tricks that can make Python code more expressive, efficient, and elegant. ...
    Downloads: 0 This Week
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  • 25
    TensorFlow Machine Learning Cookbook

    TensorFlow Machine Learning Cookbook

    Code for Tensorflow Machine Learning Cookbook

    TensorFlow Machine Learning Cookbook repository provides practical code examples and educational materials that accompany the book TensorFlow Machine Learning Cookbook. The repository contains numerous Python scripts and Jupyter notebooks that demonstrate how to implement machine learning algorithms and neural networks using the TensorFlow framework. Each section focuses on a different aspect of machine learning development, including tensor manipulation, model training, optimization strategies, and data processing techniques. ...
    Downloads: 0 This Week
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