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

  • 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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  • 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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  • 1
    Machine Learning with TensorFlow

    Machine Learning with TensorFlow

    Accompanying source code for Machine Learning with TensorFlow

    Machine Learning with TensorFlow is an open repository containing the source code and practical examples that accompany the book Machine Learning with TensorFlow. The project provides numerous code samples demonstrating how to build machine learning models using the TensorFlow framework. These examples illustrate core machine learning concepts such as regression, classification, clustering, and neural networks through practical implementations. The repository includes implementations of...
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  • 2
    Image Quality Assessment

    Image Quality Assessment

    Convolutional Neural Networks to predict aesthetic quality of images

    Image Quality Assessment is an open-source deep learning project that implements neural models for predicting the aesthetic and technical quality of digital images. The repository provides an implementation inspired by the NIMA (Neural Image Assessment) research approach, which uses convolutional neural networks trained on human-annotated datasets to estimate image quality scores. The goal of the project is to automatically evaluate images based on perceived quality factors such as...
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  • 3
    Machine Learning From Scratch

    Machine Learning From Scratch

    Bare bones NumPy implementations of machine learning models

    ...Because the code avoids external machine learning libraries, it exposes the full logic behind model training, optimization, and prediction processes. The project also provides examples and explanations that illustrate how the algorithms behave and how different components interact during training.
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  • 4
    Azure Machine Learning Python SDK

    Azure Machine Learning Python SDK

    Python notebooks with ML and deep learning examples

    Azure Machine Learning Python SDK is a curated repository of Python-based Jupyter notebooks that demonstrate how to develop, train, evaluate, and deploy machine learning and deep learning models using the Azure Machine Learning Python SDK. The content spans a wide range of real-world tasks — from foundational quickstarts that teach users how to configure an Azure ML workspace and connect to compute resources, to advanced tutorials on using pipelines, automated machine learning, and dataset handling. ...
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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
    Activity Recognition

    Activity Recognition

    Resources about activity recognition

    This repository is a curated collection of resources, papers, code, and summaries relating to human activity recognition/behavior recognition. It is not a single integrated software package but rather a knowledge base organizing feature extraction methods, deep learning approaches, transfer learning strategies, datasets, and representative research in behavior recognition. The repository includes links to code in MATLAB, Python, summaries of algorithms, datasets, and relevant research papers. ...
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  • 6
    Girls-In-AI

    Girls-In-AI

    Free learning code series: Xiaobai's introduction to Python

    Girls-In-AI is an educational repository created to encourage women and beginners to learn programming and artificial intelligence through accessible tutorials and practice materials. The project provides a collection of beginner-friendly learning resources covering Python programming, data analysis, machine learning, and deep learning topics. It aims to lower the barrier to entry for people who want to enter the field of artificial intelligence by offering structured learning paths and...
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  • 7
    TensorFlow Docs

    TensorFlow Docs

    TensorFlow latest official documentation Chinese version

    TensorFlow Docs repository maintained by the Xitu translation community provides a Chinese version of the official TensorFlow documentation. Its goal is to make the extensive TensorFlow ecosystem more accessible to developers and researchers who prefer to learn in Chinese. The repository contains translated guides, API explanations, tutorials, and conceptual documentation that mirror the structure of the original TensorFlow documentation site. Contributors from technology companies,...
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  • 8
    MIT Deep Learning

    MIT Deep Learning

    Tutorials, assignments, and competitions for MIT Deep Learning

    MIT Deep Learning is an open-source repository that contains tutorials, assignments, and learning materials related to deep learning courses taught at MIT. The repository provides hands-on tutorials that introduce the fundamental concepts behind neural networks, deep learning architectures, and modern machine learning techniques. Many of the tutorials include practical implementations that demonstrate tasks such as image classification, generative models, and neural network training...
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  • 9
    Lihang

    Lihang

    Statistical learning methods (2nd edition) [Li Hang]

    Lihang is an open-source repository that provides educational notes, mathematical derivations, and code implementations based on the book Statistical Learning Methods by Li Hang. The repository aims to help readers understand the theoretical foundations of machine learning algorithms through practical implementations and detailed explanations. It includes notebooks and scripts that demonstrate how key algorithms such as perceptrons, decision trees, logistic regression, support vector...
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  • The top-rated AI recruiting platform for faster, smarter hiring. Icon
    The top-rated AI recruiting platform for faster, smarter hiring.

    Humanly is an AI recruiting platform that automates candidate conversations, screening, and scheduling.

    Humanly is an AI-first recruiting platform that helps talent teams hire in days, not months—without adding headcount. Our intuitive CRM pairs with powerful agentic AI to engage and screen every candidate instantly, surfacing top talent fast. Built on insights from over 4 million candidate interactions, Humanly delivers speed, structure, and consistency at scale—engaging 100% of interested candidates and driving pipeline growth through targeted outreach and smart re-engagement. We integrate seamlessly with all major ATSs to reduce manual work, improve data flow, and enhance recruiter efficiency and candidate experience. Independent audits ensure our AI remains fair and bias-free, so you can hire confidently.
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  • 10
    The GAN Zoo

    The GAN Zoo

    A list of all named GANs

    The GAN Zoo is an open-source repository that compiles a comprehensive list of Generative Adversarial Network models published in research literature. The project began as a community effort to track the rapidly growing number of GAN architectures appearing in machine learning papers. Because new GAN models are frequently introduced in research publications, the repository serves as a convenient catalog that organizes them in one location. The list includes references to many GAN variants...
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  • 11
    Generative Models

    Generative Models

    Collection of generative models, e.g. GAN, VAE in Pytorch

    This project is a comprehensive open-source collection of implementations of various generative machine learning models designed to help researchers and developers experiment with deep generative techniques. The repository contains practical implementations of well-known architectures such as Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), Restricted Boltzmann Machines, and Helmholtz Machines, implemented primarily using modern deep learning frameworks like PyTorch...
    Downloads: 4 This Week
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  • 12

    TEES

    Turku Event Extraction System

    Turku Event Extraction System (TEES) is a free and open source natural language processing system developed for the extraction of events and relations from biomedical text. It is written mostly in Python, and should work in generic Unix/Linux environments. Currently, the TEES source code repository still remains on GitHub at http://jbjorne.github.com/TEES/ where there is also a wiki with more information.
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  • 13
    Spark Python Notebooks

    Spark Python Notebooks

    Apache Spark & Python (pySpark) tutorials for Big Data Analysis

    Spark Python Notebooks is a curated collection of example Jupyter notebooks designed to help developers and data engineers learn Apache Spark using Python in an interactive environment. Rather than only providing static code files, this project uses notebooks to teach practical data processing workflows, exposing users to real Spark programming patterns like working with RDDs, DataFrames, and distributed computations.
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  • 14

    HYBRYD

    Library written in C with Python API for IPv6 networking

    This project is a rewritten of an initial project that I've called GLUE and created in 2005. I'm trying to readapt it for Python 2.7.3 and GCC 4.6.3 The library has to be build as a simple Python extension using >python setup.py install and allows to create different kind of servers, clients or hybryds (clients-servers) over (TCP/UDP) using the Ipv6 Protocol. The architecture of the code is based on brain architecture. Will put an IPv6 adress active available as soon as possible so that you can download pieces of codes. ...
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  • 15

    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...
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  • 16
    pyIRDG

    pyIRDG

    IMDb Relational Dataset Generator

    pyIRDG is a program written in Python to generate relational datasets in Prolog format. It uses data from the Internet Movie Database in combination with IMDbPY as backend. A graphical user interface written in pyQt allows the user to link multiple entities together as model for the generation process. The big four entities are Title, Person, Company and Character. Many attributes can be chosen for adding to the output .pl file. Three types of constraints on attributes are available to limit...
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  • 17
    mlpy

    mlpy

    Machine Learning Python

    ...mlpy is available both for Python >=2.6 and Python 3.X.
    Downloads: 0 This Week
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  • 18
    BCI Project Triathlon
    A three-step approach towards experimental brain-computer-interfaces, based on the OCZ nia device for EEG-data acquisition and artificial neural networks for signal-interpretation.
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  • 19
    Brainiac, Is C/C++ Libraries, Programs, And Python, And Lua Scripts For Neural Networking And Genetic Programming, In An Attempt To Create A "Glue-It-All-Together" Project, Striving Towards General Artificial Intelligence
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