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15 projects for "create" with 2 filters applied:
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Go From AI Idea to AI App FastAccess Gemini 3 and 200+ models. Build chatbots, agents, or custom models with built-in monitoring and scaling.
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NVIDIA PhysicsNeMo
Open-source deep-learning framework for building and training
...The framework focuses on the emerging field of physics-informed machine learning, where neural networks are used alongside physical equations to model complex scientific systems. PhysicsNeMo provides modular Python components that allow developers to create scalable training and inference pipelines for models that combine data-driven learning with physics-based constraints. It is built on top of the PyTorch ecosystem and integrates with GPU-accelerated computing environments to handle computationally demanding simulations and datasets. The framework supports a wide range of scientific applications, including computational fluid dynamics, climate modeling, weather prediction, and engineering simulations. -
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Jina-Serve
Build multimodal AI applications with cloud-native stack
Jina Serve is an open-source framework designed for building, deploying, and scaling AI services and machine learning pipelines in production environments. The framework allows developers to create microservices that expose machine learning models through APIs that communicate using protocols such as HTTP, gRPC, and WebSockets. It is built with a cloud-native architecture that supports deployment on local machines, containerized environments, or large orchestration platforms such as Kubernetes. Jina Serve focuses on making it easier to turn machine learning models into production-ready services without forcing developers to manage complex infrastructure manually. ... -
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Learn PyTorch for Deep Learning
Materials for the Learn PyTorch for Deep Learning
...The materials include Jupyter notebooks, explanations of core deep learning concepts, and step-by-step demonstrations of building and training neural networks. Throughout the lessons, users learn how to work with tensors, create neural network architectures, manage training workflows, and evaluate model performance. -
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The Algorithms - C #
Collection of various algorithms in mathematics, machine learning
TheAlgorithms/C is an open-source repository that provides implementations of classic algorithms and data structures written in the C programming language. The project is part of the larger “The Algorithms” initiative, which aims to create educational resources by implementing algorithms in multiple programming languages. Within the C repository, contributors implement algorithms from many areas of computer science including sorting, searching, graph processing, mathematics, machine learning, and numerical methods. Each algorithm implementation is written to be readable and well documented so that students and developers can understand how the algorithm works internally. ... -
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ML Visuals
ML Visuals contains figures and templates which you can reuse
...The repository contains professional-quality figures that illustrate machine learning concepts such as neural networks, optimization methods, model architectures, and common deep learning techniques. These visuals are intended to help researchers, educators, and students create clearer presentations, blog posts, and scientific papers. The project is maintained as a collaborative community effort where contributors can add new diagrams or visual components. Many of the visuals are designed using editable formats such as Google Slides, making it easy for users to customize them for their own work. -
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Talking Head Anime from a Single Image
Demo for the "Talking Head Anime from a Single Image"
...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 create realistic animated frames while preserving the identity and appearance of the original character. The repository includes demo applications that allow users to interact with the system through graphical controls or webcam input to drive character motion. These demonstrations illustrate how generative neural rendering can be used to build real-time avatar systems for virtual characters. -
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course-v3
The 3rd edition of course.fast.ai
...The course emphasizes a top-down approach to learning artificial intelligence, where students begin by building practical models and later study the underlying theory and mathematics. The materials demonstrate how to train neural networks using the fastai library and the PyTorch deep learning framework, enabling learners to quickly create applications such as image classifiers, natural language processing models, and recommendation systems. -
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neurojs
A JavaScript deep learning and reinforcement learning library
...The library provides a full machine learning framework implemented in JavaScript that can run inside browsers or Node.js environments. It focuses particularly on reinforcement learning algorithms, enabling developers to create intelligent agents that learn through interaction with simulated environments. The framework supports neural network architectures and reinforcement learning methods such as deep Q-networks and actor-critic algorithms. Several interactive demonstrations included with the project illustrate how neural networks can be used to train agents in simulated tasks, including a browser-based self-driving car example. ... -
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...Currently, it includes the software systems KReator and MECore and the library Log4KR: - KReator is an integrated development environment (IDE) for relational probabilistic knowledge representation languages such as Bayesian Logic Programs (BLPs), Markov Logic Networks (MLNs), Relational Maximum Entropy (RME), First-Order Probabilistic Conditional Logic (FO-PCL), and others. - MECore is a shell-based system that allows the user to create propositional knowledge bases, to perform a variety of belief change operations, and to query a knowledge base with respect to the principle of optimum entropy. - Log4KR is a library providing data structures to represent knowledge bases in various logic formalisms (propositional, relational, conditional, probabilistic, ...) and providing algorithms to perform reasoning operations
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GA-EoC
GeneticAlgorithm-based search for Heterogeneous Ensemble Combinations
In data classification, there are no particular classifiers that perform consistently in every case. This is even worst in case of both the high dimensional and class-imbalanced datasets. To overcome the limitations of class-imbalanced data, we split the dataset using a random sub-sampling to balance them. Then, we apply the (alpha,beta)-k feature set method to select a better subset of features and combine their outputs to get a consolidated feature set for classifier training. To... -
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libcrn is document image processing library written in C++11 for Linux, Windows, Mac OsX and Google Android. It is a toolbox that allows to create easily software such as OCRs and layout analysis tools.
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C-IL2P
Original C-IL2P
This is a C++ implementation of the original C-IL2P system, invented by Artur D'Avila Garcez and Gerson Zaverucha. C-IL2P is a neural-symbolic learning system which uses a propositional logic program to create a three-layer recursive neural network and uses back-propagation to learn from examples. -
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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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Computer System for Adaptive Intelligent Life :: seeks to create a software system that is capable of learning. The project's ultimate goal is to further the ability of software to both adapt to individual users, and to respond their needs.
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This is an attempt to create simple image recognition program in java. Demo here: http://www.youtube.com/watch?v=N4m4j4D3pJU
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