Search Results for "learning" - Page 96
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Showing 4736 open source projects for "learning"
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Go from Code to Production URL in SecondsSkip the Kubernetes configs. Cloud Run handles HTTPS, scaling, and infrastructure automatically. Two million requests free per month.
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Resea
A microkernel-based hackable operating system
...Written in C with minimal dependencies, it emphasizes modularity, isolation, and simplicity. resea includes a basic POSIX-like interface and supports multitasking, IPC, and user-space services. It serves as both a microkernel OS experiment and a platform for learning about low-level system design without the complexity of larger operating systems. -
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LingL
clone of lingq to learn new language
Learn new languages by reading anything you choose. This was inspired by other site/projects like the opensource Lwt, the closed source lingq etc... MAIN SITE IS ON GITHUB (for releases, issues etc...): https://github.com/gustavklopp/LingL -
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XZVoice
Free and open source text-to-speech software
...Technically, multi-level rhythmic pauses are taken into account to achieve the purpose of natural synthesizing rhythm, and comprehensively use acoustic parameters and linguistic parameters to establish multiple automatic prediction models based on deep learning. Using massive audio data to train the pronunciation model, the synthetic sound is real, full, cadenced, and expressive, and the MOS score has reached the professional level in the industry. -
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Demo Scene
Scripts and samples to support Confluent Demos, Talks, and Blogs
Demo Scene is a collection of resources and examples provided by Confluent Inc. to demonstrate the capabilities of Apache Kafka and its ecosystem. It includes various demos showcasing real-time data streaming, processing, and integration patterns -
Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
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Awesome Graph Classification
Graph embedding, classification and representation learning papers
A collection of graph classification methods, covering embedding, deep learning, graph kernel and factorization papers with reference implementations. Relevant graph classification benchmark datasets are available. Similar collections about community detection, classification/regression tree, fraud detection, Monte Carlo tree search, and gradient boosting papers with implementations. -
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Universal Data Tool
Collaborate & label any type of data, images, text, or documents etc.
...Import from your S3 buckets easily with IAM or Cognito authentication. Working together, we can accomplish more. The Universal Data Tool was built to bring together the best ideas from different machine learning communities. Upload your dataset to Courses to create a training course. Testing and exercises validate that your workforce knows exactly how the data should be labeled. Get started in less than a minute. Courses uses administrator links. No sign up needed. -
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BerryNet
Deep learning gateway on Raspberry Pi and other edge devices
This project turns edge devices such as Raspberry Pi into an intelligent gateway with deep learning running on it. No internet connection is required, everything is done locally on the edge device itself. Further, multiple edge devices can create a distributed AIoT network. At DT42, we believe that bringing deep learning to edge devices is the trend towards the future. It not only saves costs of data transmission and storage but also makes devices able to respond according to the events shown in the images or videos without connecting to the cloud. ... -
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DeltaOS
Just another Arch based Linux distribution.
Delta OS is an Arch based distribution created for developers and people intrested in Arch Linux. It is created by the Delta OS team which is led by Mr. Apurba Adhikari. Due to Arch Linux having good amount of learning curve and a complex installation procedure, Delta OS tries to simplify it and brings a bit user friendly and beautiful interface giving almost same Arch experience. Delta OS comes built in with VS Code, Sublime, NodeJS and OpenJDK preinstalled for developers. In later version, our team is also planning to integrate Docker and Anaconda built-in. ... -
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Self-Attentive Parser
High-accuracy NLP parser with models for 11 languages
LightAutoML is an automated machine learning (AutoML) framework developed by Sberbank AI Lab, designed to facilitate the development of machine learning models with minimal human intervention. -
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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Data Science Notes
Curated collection of data science learning materials
Data Science Notes is a large, curated collection of data science learning materials, with explanations, code snippets, and structured notes across the typical end-to-end workflow. It spans foundational math and statistics through data wrangling, visualization, machine learning, and practical project organization. The content emphasizes hands-on understanding by pairing narrative notes with runnable examples, making it useful for both self-study and classroom settings. ... -
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Awesome Community Detection Research
A curated list of community detection research papers
A collection of community detection papers. A curated list of community detection research papers with implementations. Similar collections about graph classification, classification/regression tree, fraud detection, and gradient boosting papers with implementations. -
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MachineLearningStocks
Using python and scikit-learn to make stock predictions
MachineLearningStocks is a Python-based template project that demonstrates how machine learning can be applied to predicting stock market performance. The project provides a structured workflow that collects financial data, processes features, trains predictive models, and evaluates trading strategies. Using libraries such as pandas and scikit-learn, the repository shows how historical financial indicators can be transformed into machine learning features. -
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TTS
Deep learning for text to speech
TTS is a library for advanced Text-to-Speech generation. It's built on the latest research, was designed to achieve the best trade-off among ease-of-training, speed, and quality. TTS comes with pre-trained models, tools for measuring dataset quality, and is already used in 20+ languages for products and research projects. Released models in PyTorch, Tensorflow and TFLite. Tools to curate Text2Speech datasets underdataset_analysis. Demo server for model testing. Notebooks for extensive model... -
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hplayer
A multi-screen player using Qt + FFmpeg
...It focuses on providing a minimal yet functional implementation of video playback, including decoding, rendering, and synchronization. The project is structured as a learning resource, helping developers understand the fundamentals of multimedia pipelines. It supports common audio and video formats and includes playback controls for managing media streams. The architecture emphasizes performance and simplicity, using native libraries to achieve efficient playback. It also demonstrates integration between UI layers and low-level media processing components. ... -
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PyTorch SimCLR
PyTorch implementation of SimCLR: A Simple Framework
For quite some time now, we know about the benefits of transfer learning in Computer Vision (CV) applications. Nowadays, pre-trained Deep Convolution Neural Networks (DCNNs) are the first go-to pre-solutions to learn a new task. These large models are trained on huge supervised corpora, like the ImageNet. And most important, their features are known to adapt well to new problems. This is particularly interesting when annotated training data is scarce. -
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Emerald
An operating system written in C
emerald is a minimalistic Unix-like operating system kernel developed for x86_64 systems, focused on being lightweight, modular, and understandable. Written in C and assembly, emerald serves as a learning tool for OS enthusiasts who want to explore kernel design from scratch. It includes basic components such as multitasking, paging, interrupts, and system calls, while maintaining a clear and concise codebase. Emerald is a strong starting point for building more complex systems or experimenting with new OS features. -
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HamsterLab
education, children, course, C programming language, maze, 2d graphic
This project is meant to particularly support children in learning the C programming language by developing different kinds of hamster-based games in a 2D graphics environment. It is designed to be used for teaching classes and contains a possible lesson plan (currently only in German). Special thanks to Oliver Saalfeld for drawing the texture graphics. Please note that the software is not finished, yet, since it is developed right now in parallel to my current course. ... -
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PORORO
Platform of neural models for natural language processing
pororo performs Natural Language Processing and Speech-related tasks. It is easy to solve various subtasks in the natural language and speech processing field by simply passing the task name. Recognized speech sentences using the trained model. Currently English, Korean and Chinese support. Get vector or find similar words and entities from pretrained model using Wikipedia. -
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Keras TCN
Keras Temporal Convolutional Network
TCNs exhibit longer memory than recurrent architectures with the same capacity. Performs better than LSTM/GRU on a vast range of tasks (Seq. MNIST, Adding Problem, Copy Memory, Word-level PTB...). Parallelism (convolutional layers), flexible receptive field size (possible to specify how far the model can see), stable gradients (backpropagation through time, vanishing gradients). The usual way is to import the TCN layer and use it inside a Keras model. The receptive field is defined as the... -
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X32 Scene Parser
An X32 scene management tool
This parsing tool can be used to extract sections of a Behringer X32 or Midas M32 scene file in order to create specialized snippets. -
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jdw pool tips
Pool Tips
Pool (billiards) instructional sheets and tips, in PDF files. Free and open for anyone learning to play pool. -
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X-Air Scene Parser
An X-Air scene management tool
The X-Air/M-Air does not include snippets (like the X32), This parsing tool is a port of the X32 Scene Parser that can be used to create modified scene files which can function like snippets. -
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TensorLayer
Deep learning and reinforcement learning library for scientists
TensorLayer is a novel TensorFlow-based deep learning and reinforcement learning library designed for researchers and engineers. It provides an extensive collection of customizable neural layers to build advanced AI models quickly, based on this, the community open-sourced mass tutorials and applications. TensorLayer is awarded the 2017 Best Open Source Software by the ACM Multimedia Society. -
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BudgetML
Deploy a ML inference service on a budget in 10 lines of code
...BudgetML is perfect for practitioners who would like to quickly deploy their models to an endpoint, but not waste a lot of time, money, and effort trying to figure out how to do this end-to-end. We built BudgetML because it's hard to find a simple way to get a model in production fast and cheaply. Deploying from scratch involves learning too many different concepts like SSL certificate generation, Docker, REST, Uvicorn/Gunicorn, backend servers etc., that are simply not within the scope of a typical data scientist. BudgetML is our answer to this challenge. It is supposed to be fast, easy, and developer-friendly. It is by no means meant to be used in a full-fledged production-ready setup. ... -
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Neurolinux
Neurolinux, the Deep Learning OS
Neurolinux, the Deep Learning OS, with all necessary tools and libraries pre-installed. Pytorch, Tensorflow Jupyter notebooks...etc