Search Results for "learning" - Page 85
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Showing 4736 open source projects for "learning"
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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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99.99% Uptime for MySQL and PostgreSQL DatabasesCloud SQL Enterprise Plus delivers near-zero downtime with 35 days of point-in-time recovery. Supports MySQL, PostgreSQL, and SQL Server.
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Guide to Technical Interviews
Guided collection and roadmap for preparing technical interviews
This repository is a guided collection and roadmap for preparing technical interviews, covering the gamut from algorithmic challenges and data structures to system design and behavioral preparation. It consolidates resources like interview question lists, practice platforms, mock interview sites, and recommended books or blogs. For individuals targeting big-tech or rigorous interview processes, this acts as a structured study guide rather than a random list of links. The README breaks down... -
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Video Pre-Training
Learning to Act by Watching Unlabeled Online Videos
The Video PreTraining (VPT) repository provides code and model artifacts for a project where agents learn to act by watching human gameplay videos—specifically, gameplay of Minecraft—using behavioral cloning. The idea is to learn general priors of control from large-scale, unlabeled video data, and then optionally fine-tune those priors for more goal-directed behavior via environment interaction. The repository contains demonstration models of different widths, fine-tuned variants (e.g. for... -
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StudioGAN
StudioGAN is a Pytorch library providing implementations of networks
StudioGAN is a Pytorch library providing implementations of representative Generative Adversarial Networks (GANs) for conditional/unconditional image generation. StudioGAN aims to offer an identical playground for modern GANs so that machine learning researchers can readily compare and analyze a new idea. Moreover, StudioGAN provides an unprecedented-scale benchmark for generative models. The benchmark includes results from GANs (BigGAN-Deep, StyleGAN-XL), auto-regressive models (MaskGIT, RQ-Transformer), and Diffusion models (LSGM++, CLD-SGM, ADM-G-U). StudioGAN is a self-contained library that provides 7 GAN architectures, 9 conditioning methods, 4 adversarial losses, 13 regularization modules, 6 augmentation modules, 8 evaluation metrics, and 5 evaluation backbones. ... -
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* To cite this dataset refer to http://dx.doi.org/10.12785/ijcds/130177 Mazari, A. C., & Kheddar, H. (2023). "Deep Learning-based Analysis of Algerian Dialect Dataset Targeted Hate Speech, Offensive Language and Cyberbullying." IJCDS, 13(1). * Due to the nature of this Dataset, comments contain offensiveness and hate speech. This does not reflect author values, however the aim is to providing a resource to help in detecting and preventing spread of such harmful content.
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Augmentor.jl
A fast image augmentation library in Julia for machine learning
A fast library for increasing the number of training images by applying various transformations. Augmentor is a real-time image augmentation library designed to render the process of artificial dataset enlargement more convenient, less error prone, and easier to reproduce. It offers the user the ability to build a stochastic image-processing pipeline (or simply augmentation pipeline) using image operations as building blocks. In other words, an augmentation pipeline is little more but a... -
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Acid Game Engine
A high speed C++17 Vulkan game engine
Acid is an open-source project listed on GitHub, but as of now its public presence is minimal (few stars, limited documentation), and there is little publicly available description of its scope or design intentions beyond repository contents. As such it appears to be a small-scale or early-stage engine or toolkit — perhaps experimental — rather than a mature, widely-adopted framework. Because of the lack of detailed docs, it’s hard to say exactly what kinds of games/applications it targets,... -
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Alphafold2
Unofficial Pytorch implementation / replication of Alphafold2
To eventually become an unofficial working Pytorch implementation of Alphafold2, the breathtaking attention network that solved CASP14. Will be gradually implemented as more details of the architecture is released. Once this is replicated, I intend to fold all available amino acid sequences out there in-silico and release it as an academic torrent, to further science. Deepmind has open sourced the official code in Jax, along with the weights! This repository will now be geared towards a... -
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Linux-Tutorial
Learning repository written from the perspective of a Java programmer
Linux-Tutorial is a Simplified Chinese Linux learning repository written from the perspective of a Java programmer. It aims to help more developers enter the Linux world by organizing practical notes, installation guides, command references, and server setup material. The content covers Linux basics, Ubuntu, CentOS, Kali Linux, VMware, Vim, SSH, Bash, Sed, compression tools, Yum, Zsh, and many development operations topics. -
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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. -
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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Deep learning time series forecasting
Deep learning PyTorch library for time series forecasting
Example image Flow Forecast (FF) is an open-source deep learning for time series forecasting framework. It provides all the latest state-of-the-art models (transformers, attention models, GRUs) and cutting-edge concepts with easy-to-understand interpretability metrics, cloud provider integration, and model serving capabilities. Flow Forecast was the first time series framework to feature support for transformer-based models and remains the only true end-to-end deep learning for time series forecasting framework. ... -
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100+ Python Projects Challenge
100+ Python Projects Challenge
100+ Python Projects Challenge is a project-based Python learning repository focused on building many small applications and utilities. Instead of only practicing isolated syntax, it encourages learners to apply Python through complete mini-projects. The challenges span practical scripts, beginner applications, automation ideas, games, data tasks, and other hands-on exercises. This makes it useful for users who want to build a portfolio of small programs while reinforcing programming fundamentals. ... -
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GPCS4
A work-in-progress PlayStation 4 emulator
A PlayStation 4 emulator which was just started. A project done for fun, and for technical research. The only reason I have started this project is for learning 3D graphics. It's not intended to become a serious application. Support simple compute shader, compute ring, cube maps. For more details you could join our discord server to contact me, or if you are used to Tencent QQ/TIM, just join our group. There you can get more resources which are useful for contributing. To run or develop GPCS4, a CPU supporting AVX instruction set as well as a graphics card supporting Vulkan 1.3 are required. -
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the-way-to-go_ZH_CN
The Chinese translation of "The Way to Go" Guide
the-way-to-go_ZH_CN is the Chinese translation of the Go programming book The Way to Go, known as (“Go Introduction Guide”). The translator, along with a team of contributors, created this project to make a high-quality Go learning resource accessible to Chinese readers who might struggle with English-language books. The README explains that the original author, Ivo Balbaert, granted authorization for the translation and even for updating certain content to match newer Go versions. The repository is structured like a full book: there are directories for cover and eBook materials, a table of contents file (TOC.md), configuration for building, and the chapters themselves in Markdown. ... -
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Fairseq
Facebook AI Research Sequence-to-Sequence Toolkit written in Python
Fairseq(-py) is a sequence modeling toolkit that allows researchers and developers to train custom models for translation, summarization, language modeling and other text generation tasks. We provide reference implementations of various sequence modeling papers. Recent work by Microsoft and Google has shown that data parallel training can be made significantly more efficient by sharding the model parameters and optimizer state across data parallel workers. These ideas are encapsulated in the... -
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ModelFox
ModelFox makes it easy to train, deploy, and monitor ML models
ModelFox makes it easy to train, deploy, and monitor machine learning models. Train a model from a CSV file on the command line. Make predictions from Elixir, Go, JavaScript, PHP, Python, Ruby, or Rust. Learn about your models and monitor them in production from your browser. ModelFox makes it easy to train, deploy, and monitor machine learning models. You can install the modelfox CLI by either downloading the binary from the latest GitHub release or by building from source. ... -
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SageMaker MXNet Inference Toolkit
Toolkit for allowing inference and serving with MXNet in SageMaker
...The AWS DLCs are used in Amazon SageMaker as the default vehicles for your SageMaker jobs such as training, inference, transforms etc. They've been tested for machine learning workloads on Amazon EC2, Amazon ECS and Amazon EKS services as well. -
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Catalyst
Accelerated deep learning R&D
Catalyst is a PyTorch framework for accelerated Deep Learning research and development. It allows you to write compact but full-featured Deep Learning pipelines with just a few lines of code. With Catalyst you get a full set of features including a training loop with metrics, model checkpointing and more, all without the boilerplate. Catalyst is focused on reproducibility, rapid experimentation, and codebase reuse so you can break the cycle of writing another regular train loop and make something totally new. ... -
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pyprobml
Python code for "Probabilistic Machine learning" book by Kevin Murphy
Python 3 code to reproduce the figures in the books Probabilistic Machine Learning: An Introduction (aka "book 1") and Probabilistic Machine Learning: Advanced Topics (aka "book 2"). The code uses the standard Python libraries, such as numpy, scipy, matplotlib, sklearn, etc. Some of the code (especially in book 2) also uses JAX, and in some parts of book 1, we also use Tensorflow 2 and a little bit of Torch. See also probml-utils for some utility code that is shared across multiple notebooks. -
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pyTorch Tutorials
Build your neural network easy and fast
...The project is structured around clear, executable Python scripts and Jupyter notebooks that demonstrate regression, classification, convolutional networks, recurrent networks, autoencoders, and generative adversarial networks, which gives learners practical exposure to real machine learning tasks. Each example explains PyTorch’s dynamic computation graph, optimization techniques, and core abstractions in a way that is accessible and reproducible. Contributors and authors integrate visual and coded examples so readers can see both the theory and the implementation side-by-side. -
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ml5.js
Friendly machine learning for the web
A neighborly approach to creating and exploring artificial intelligence in the browser. ml5.js aims to make machine learning approachable for a broad audience of artists, creative coders, and students. The library provides access to machine learning algorithms and models in the browser, building on top of TensorFlow.js with no other external dependencies. -
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paip-lisp
Lisp code for the textbook "Paradigms of Artificial Intelligence"
...It is valuable for readers who want to study the original code while working through the text or revisiting older AI ideas. The code also serves as a historical reference for how AI programming was taught before today’s deep-learning-centered ecosystem. paip-lisp is best suited for learners interested in Lisp, symbolic AI, and the foundations of practical AI programming. -
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starboard-notebook
In-browser literate notebooks
...Starboard notebooks support multiple languages, and the tooling emphasizes portability, making notebooks viewable and executable even on mobile devices or static sites. Because the runtime runs entirely inside the browser, it removes installation barriers and provides a sandboxed environment for exploration, learning, and sharing. The project plays into a larger ecosystem of in-browser computation and literate programming tools, helping users publish interactive content on the web with minimal setup. -
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ASRT Speech Recognition
A Deep-Learning-Based Chinese Speech Recognition System
ASRT is an end-to-end deep-learning Chinese ASR system built with TensorFlow/Keras, using convolution + CTC and a Max-Entropy HMM language model. It provides a REST/gRPC server backend and client SDKs in multiple languages (Python, Java, Go, Windows). Notably lightweight, it performs well without needing GPU acceleration and runs across platforms, targeting developers and researchers building Chinese voice interfaces. -
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DeepLearning Tutorial
Deep Learning Tutorial, Excellent Articles, Deep Learning Tutorial
DeepLearning is an open-source repository that aggregates tutorials, articles, and educational resources related to deep learning and machine learning. The project is designed as a knowledge collection that helps beginners understand neural networks, deep learning architectures, and fundamental machine learning concepts. It contains curated learning materials covering topics such as feedforward neural networks, activation functions, backpropagation algorithms, optimization methods, and convolutional neural networks. ... -
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MyABCs
Learn the English alphabet
An educational game for young children. MyABCs familiarizes children with the English alphabet and a keyboard.