Search Results for "learning" - Page 78
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Showing 4736 open source projects for "learning"
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PARL
A high-performance distributed training framework
PARL is a scalable reinforcement learning framework built on top of PaddlePaddle. It focuses on modularity and ease of use, supporting distributed training and a variety of RL algorithms. -
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TinyEngine
Tiny OpenGL Wrapper / 3D Engine in C++
TinyEngine is a small, self-contained OpenGL-based 3D engine written in C, designed for learning and prototyping graphics applications. It packs a lot of functionality into a compact codebase, making it ideal for exploring 3D rendering, game development, and shader programming without the overhead of larger engines. Despite its size, TinyEngine supports modern OpenGL features, texture mapping, lighting, and audio, providing a practical foundation for building lightweight 3D experiences. -
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Simple LLM Finetuner
Simple UI for LLM Model Finetuning
...The tool includes a web-based interface where users can input datasets, configure training parameters, and run fine-tuning jobs without deep knowledge of machine learning pipelines. It leverages libraries such as Hugging Face PEFT to enable efficient adaptation of models by modifying only a subset of parameters, significantly reducing computational requirements. In addition to training, the platform provides inference capabilities so users can immediately test and evaluate their fine-tuned models within the same environment. -
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PIFuHD
High-Resolution 3D Human Digitization from A Single Image
PIFuHD (Pixel-Aligned Implicit Function for 3D human reconstruction at high resolution) is a method and codebase to reconstruct high-fidelity 3D human meshes from a single image. It extends prior PIFu work by increasing resolution and detail, enabling fine geometry in cloth folds, hair, and subtle surface features. The method operates by learning an implicit occupancy / surface function conditioned on the image and camera projection; at inference time it queries dense points to reconstruct a mesh via marching cubes. It also uses a two-stage architecture: a coarse global model followed by local refinement patches to capture fine detail, balancing global consistency and local detail. ... -
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ML Course Notes
Collaborative machine learning lecture notes from top AI courses
ML-Course-Notes is a collaborative repository that collects and organizes lecture notes covering a wide range of machine learning and artificial intelligence topics. It serves as a centralized resource where contributors share summaries and written notes derived from well-known machine learning courses. These notes cover subjects such as supervised learning, deep learning, neural networks, natural language processing, and reinforcement learning. ML-Course-Notes organizes content according to specific courses and lectures, allowing learners to navigate through structured educational material more easily. ... -
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NAM-Runner
Batch file to install and run NAM (neural-amp-modeler) easily.
A Windows 10 batch file, that installs and runs the NAM model trainer (neural-amp-modeler) by Steven Atkinson right into the GUI application. Fully automated. Custom one-time installation of everything you need to train neural network models of guitar amps and more for the NAM VST plugin, no Conda required. Runs as a launcher afterwards. Portable installation. New pyTorch inclues CUDA runtime for fast Nvidia GPU support. No command line, python or conda knowledge needed! Just double click. -
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PromptPapers
Curated list of prompt-learning papers for NLP research use
PromptPapers is a curated repository that collects and organizes influential research papers focused on prompt-based tuning for large-scale pre-trained language models. It serves as a centralized reading list for researchers and practitioners interested in modern prompt learning techniques, which differ from traditional fine-tuning by leveraging pre-trained tasks directly for prediction. PromptPapers categorizes papers into multiple sections such as overview, pilot work, basics, analysis, improvements, and specializations, helping users navigate the evolution of the field systematically. It also includes keyword conventions to describe each paper’s methods, tasks, and properties, making it easier to compare different approaches. ... -
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Keras Attention Mechanism
Attention mechanism Implementation for Keras
Many-to-one attention mechanism for Keras. We demonstrate that using attention yields a higher accuracy on the IMDB dataset. We consider two LSTM networks: one with this attention layer and the other one with a fully connected layer. Both have the same number of parameters for a fair comparison (250K). The attention is expected to be the highest after the delimiters. An overview of the training is shown below, where the top represents the attention map and the bottom the ground truth. As the... -
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Remix IDE
Browser-based compiler and IDE
...It fosters a fast development cycle and has a rich set of plugins with intuitive GUIs. Remix is used for the entire journey of contract development as well as act as a playground for learning and teaching Ethereum. Remix IDE is part of the Remix Project which is a platform for development tools that use a plugin architecture. It encompasses sub-projects including Remix Plugin Engine, Remix Libs, and of course Remix-IDE. Remix IDE is a powerful open source tool that helps you write Solidity contracts straight from the browser. ... -
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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Knet
Koç University deep learning framework
Knet.jl is a deep learning package implemented in Julia, so you should be able to run it on any machine that can run Julia. It has been extensively tested on Linux machines with NVIDIA GPUs and CUDA libraries, and it has been reported to work on OSX and Windows. If you would like to try it on your own computer, please follow the instructions on Installation. -
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FFCV
Fast Forward Computer Vision (and other ML workloads!)
ffcv is a drop-in data loading system that dramatically increases data throughput in model training. From gridding to benchmarking to fast research iteration, there are many reasons to want faster model training. Below we present premade codebases for training on ImageNet and CIFAR, including both (a) extensible codebases and (b) numerous premade training configurations. -
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Lumixon
This AI can answer any information based questions from the user.
1. This AI is not yet prepared for human interactions or chatting. 2. The AI produces the complete information regarding the user's question and if you wish to search for another new question, you need to close and run the application again. This feature will be changed in the next release 3. Download and extract the files to your desired location and run the exe file in order to run the application. 4. The AI prints the website(s) links if it is unable to get an answer for the... -
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ArtLine
Deep learning tool that converts portrait photos into line art
ArtLine is a deep learning-based project focused on generating high-quality line art portraits from input images. It leverages neural network techniques built on top of the fastai library and PyTorch to transform photographic portraits into stylized line drawings. ArtLine is trained using datasets such as APDrawing and anime sketch colorization pairs to better understand facial structures and artistic line representation. -
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OptiMate
Libraries for optimizing AI models, inference speed, and GPU usage
Optimate is an open source collection of libraries designed to optimize the performance and cost efficiency of artificial intelligence models across different stages of the machine learning lifecycle. It groups several internal optimization tools developed by Nebuly AI into a single repository that focuses on improving inference speed, reducing infrastructure usage, and streamlining model training workflows. Its modules help developers automatically apply optimization techniques that better align AI models with the capabilities of the underlying hardware such as GPUs and CPUs. ... -
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Image To Gerber Converter
Convert any image to gerber and drill files
ImageToGerber makes it easy to convert any image to gerber files, ready to send to a PCB manufacturer. More info at: https://www.imagetopcb.com Demo video: https://youtu.be/HUvt0mOHv_M Forget about spending long hours etching and drilling at home, or learning to use complicated CAD software, schematics, layout design,… And more importantly, ImageToPCB is more than just a converter, it expands the potential of your design or image. It unlocks the possibility to easily make improvements and updating your design, as you will be able to make design modifications, add a silkscreen layer, resize drill diameters, create a soldermask layer to protect copper areas and to avoid accidental shorts, convert a single-side design into a double-side or multi-layer design,… all that just by editing your image with your preferred image editor. -
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GPT-NeoX
Implementation of model parallel autoregressive transformers on GPUs
This repository records EleutherAI's library for training large-scale language models on GPUs. Our current framework is based on NVIDIA's Megatron Language Model and has been augmented with techniques from DeepSpeed as well as some novel optimizations. We aim to make this repo a centralized and accessible place to gather techniques for training large-scale autoregressive language models, and accelerate research into large-scale training. For those looking for a TPU-centric codebase, we... -
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XLabel
XLabel: An Explainable Data Labeling Assistant
XLabel is an open-source Streamlit app that takes an explainable machine-learning approach to visual-interactive data labeling. Predict the most probable labels using Explainable Boosting Machine (EBM). Show the contributions of each feature towards the predicted labels. Provide an option to write the labels directly into the data file (use XLabel.py) or save them in a separate file (use XLabelDL.py) Support data with multiple labels and multiple classes. -
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Merlion
A Machine Learning Framework for Time Series Intelligence
Merlion is a Python library for time series intelligence. It provides an end-to-end machine learning framework that includes loading and transforming data, building and training models, post-processing model outputs, and evaluating model performance. It supports various time series learning tasks, including forecasting, anomaly detection, and change point detection for both univariate and multivariate time series. This library aims to provide engineers and researchers a one-stop solution to rapidly develop models for their specific time series needs, and benchmark them across multiple time series datasets. -
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LifeAI is an artificial intelligence system that can be applied to robotics, games, or business. It simulates key processes of our minds, such as organizing data into concepts and categories, planning actions based on their predicted outcome, and communication. LifeAI was designed to be simple, but powerful and flexible enough to have many applications.
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ACHE Focused Crawler
ACHE is a web crawler for domain-specific search
...ACHE differs from generic crawlers in sense that it uses page classifiers to distinguish between relevant and irrelevant pages in a given domain. A page classifier can be defined as a simple regular expression (e.g., that matches every page that contains a specific word) or a machine-learning-based classification model. ACHE also automatically learns how to prioritize links in order to efficiently locate relevant content while avoiding the retrieval of irrelevant pages. While ACHE was originally designed to perform focused crawls, it also supports other crawling tasks, including crawling all pages in a given web site and crawling Dark Web sites (using the TOR protocol). -
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php-billing-app
A basic PHP/MySQL/HTML Billing APP. Meant for developers learning.
Here is PHP/MySQL/HTML code that is a sample Entry Level Billing APP. It is Free, and mostly for learning purposes. You can install on a Windows or linux server, and look at the PHP code files on your PC. -
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ElegantRL
Massively Parallel Deep Reinforcement Learning
ElegantRL is an efficient and flexible deep reinforcement learning framework designed for researchers and practitioners. It focuses on simplicity, high performance, and supporting advanced RL algorithms. -
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auto-sklearn
Automated machine learning with scikit-learn
auto-sklearn is an automated machine learning toolkit and a drop-in replacement for a scikit-learn estimator. auto-sklearn frees a machine learning user from algorithm selection and hyperparameter tuning. It leverages recent advantages in Bayesian optimization, meta-learning and ensemble construction. Auto-sklearn 2.0 includes latest research on automatically configuring the AutoML system itself and contains a multitude of improvements which speed up the fitting the AutoML system. auto-sklearn 2.0 works the same way as regular auto-sklearn. auto-sklearn is licensed the same way as scikit-learn, namely the 3-clause BSD license. -
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Alpa
Training and serving large-scale neural networks
Alpa is a system for training and serving large-scale neural networks. Scaling neural networks to hundreds of billions of parameters has enabled dramatic breakthroughs such as GPT-3, but training and serving these large-scale neural networks require complicated distributed system techniques. Alpa aims to automate large-scale distributed training and serving with just a few lines of code. -
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Unitag is a language-independent Unicode-based part-of-speech tagging system. Written entirely in ANSI-compatible C, it should (in theory) compile on any OS, but has been tested on 32-bit Windows.