Search Results for "self learning" - Page 9
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Showing 337 open source projects for "self 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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Fully Managed MySQL, PostgreSQL, and SQL ServerCloud SQL handles your database ops end to end, so you can focus on your app.
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CPT
CPT: A Pre-Trained Unbalanced Transformer
A Pre-Trained Unbalanced Transformer for Both Chinese Language Understanding and Generation. We replace the old BERT vocabulary with a larger one of size 51271 built from the training data, in which we 1) add missing 6800+ Chinese characters (most of them are traditional Chinese characters); 2) remove redundant tokens (e.g. Chinese character tokens with ## prefix); 3) add some English tokens to reduce OOV. Position Embeddings We extend the max_position_embeddings from 512 to 1024. We... -
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albert_zh
Implementation of A Lite Bert For Self-Supervised Learning Language
albert_zh is a Chinese ALBERT pretraining and model release repository. It implements ALBERT with TensorFlow and provides Chinese pretrained models designed to reduce parameter size while preserving strong language understanding performance. The project includes several model variants, such as tiny, small, base, large, and xlarge-style releases, giving users options for speed, size, and accuracy tradeoffs. It also provides guidance for fine-tuning downstream tasks such as sentence-pair... -
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Shennina
Automating Host Exploitation with AI
Shennina is an automated host exploitation framework. The mission of the project is to fully automate the scanning, vulnerability scanning/analysis, and exploitation using Artificial Intelligence. Shennina is integrated with Metasploit and Nmap for performing the attacks, as well as being integrated with an in-house Command-and-Control Server for exfiltrating data from compromised machines automatically. Shennina scans a set of input targets for available network services, uses its AI engine... -
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Rakkas
Bleeding-edge React framework powered by Vite
...If you need a stable React framework try Next.js, Remix, or Gatsby. create-rakkas-app project initializer comes with many features, all of which are optional but we strongly recommend enabling TypeScript and the generation of a demo project on your first try because self-documenting type definitions allow for a smoother learning curve and the demo project source code comes with plenty of comments. -
Demo Series - Small Business Backup By VeeamWatch this on-demand demo series and learn how to protect your Microsoft 365 data with clear, simple, actionable steps that are easy to implement for businesses of all sizes.
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Vulnhub-CTF-Writeups
This cheasheet is aimed at CTF Players to sort Vulnhub Labs
Vulnhub CTF Writeups is a curated collection of walkthrough references for intentionally vulnerable VulnHub virtual machines. It targets beginners and CTF players who want organized practice material for penetration-testing labs. The repository gathers Hacking Articles solutions into one large directory instead of requiring users to locate each article separately. Its catalog includes well-known series such as Kioptrix, SickOS, DC, pWnOS, LAMPSecurity, and many other community machines. Each... -
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DeepMind Educational Resources
DeepMind's repo of educational notebooks for learning AI and research
Educational is an open collection of interactive tutorials created by Google DeepMind to make the fundamentals of machine learning and artificial intelligence accessible to learners of all backgrounds. The repository provides hands-on, beginner-friendly resources that introduce essential AI concepts through Google Colab notebooks, combining intuitive explanations with executable code. The tutorials cover a broad range of topics—from foundational Python programming and data handling to supervised, unsupervised, and reinforcement learning, as well as graph neural networks and scientific reasoning. ... -
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BEVFormer
Implementation of BEVFormer, a camera-only framework
3D visual perception tasks, including 3D detection and map segmentation based on multi-camera images, are essential for autonomous driving systems. In this work, we present a new framework termed BEVFormer, which learns unified BEV representations with spatiotemporal transformers to support multiple autonomous driving perception tasks. In a nutshell, BEVFormer exploits both spatial and temporal information by interacting with spatial and temporal space through predefined grid-shaped BEV... -
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Reskin Sensor Library
ReSkin Sensor Interfacing Library
...However, the same properties of conformal contact result in faster deterioration of soft sensors and larger variations in their response characteristics over time and across samples, inhibiting their ability to be long-lasting and replaceable. ReSkin is a tactile soft sensor that leverages machine learning and magnetic sensing to offer a low-cost, diverse and compact solution for long-term use. Magnetic sensing separates the electronic circuitry from the passive-interface, making it easier to replace interfaces as they wear out while allowing for a wide variety of form factors. Machine learning allows us to learn sensor response models that are robust to variations across fabrication and time, and our self-supervised learning algorithm enables finer performance enhancement. -
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golangweekly
Weekly magazine for Go language lovers, published every Sunday
As Go has received more and more attention, there have been more and more related articles, software, and resources. Go Language Lovers Weekly aims to share with you a week of Go language-related content that is worth knowing and learning. Published every Sunday. Contributions, recommended or self-recommended articles/software/resources are welcome, please submit an issue. Welcome to pay attention to our public account and get the weekly magazine as soon as possible. Weekly magazine for Go language lovers, published every Sunday. -
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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TeachYourselfCS-CN
A Chinese translation of TeachYourselfCS
TeachYourselfCS-CN is a Chinese translation of the Teach Yourself Computer Science curriculum for independent learners. It is aimed at self-taught developers, bootcamp graduates, students, and engineers seeking stronger computer science foundations. The guide recommends a focused sequence of core subjects instead of presenting an unfiltered collection of courses. Topics include programming, computer architecture, algorithms, mathematics, operating systems, networking, databases, compilers,... -
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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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Brain Tokyo Workshop
Experiments and code from Google Brain’s Tokyo research workshop
The Brain Tokyo Workshop repository hosts a collection of research materials and experimental code developed by the Google Brain team based in Tokyo. It showcases a variety of cutting-edge projects in artificial intelligence, particularly in the areas of neuroevolution, reinforcement learning, and model interpretability. Each project explores innovative approaches to learning, prediction, and creativity in neural networks, often through unconventional or biologically inspired methods. The repository includes implementations, experimental data, and supporting research papers that accompany published studies. Notable works such as Weight Agnostic Neural Networks and Neuroevolution of Self-Interpretable Agents highlight the team’s exploration of how AI can learn more efficiently and transparently. ... -
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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. It allows researchers and developers to train... -
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MAE (Masked Autoencoders)
PyTorch implementation of MAE
MAE (Masked Autoencoders) is a self-supervised learning framework for visual representation learning using masked image modeling. It trains a Vision Transformer (ViT) by randomly masking a high percentage of image patches (typically 75%) and reconstructing the missing content from the remaining visible patches. This forces the model to learn semantic structure and global context without supervision. -
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30 Days of Elixir
A walk through the Elixir language in 30 exercises
...This incremental learning format allows developers to build confidence and understanding while maintaining consistent progress. As one of the early and influential resources in the Elixir community, 30-days-of-elixir remains a valuable guide for self-learners and newcomers to the functional programming paradigm. -
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Deep Learning Papers Reading Roadmap
Deep Learning papers reading roadmap for anyone who are eager to learn
Deep Learning Papers Reading Roadmap is a widely known curated reading plan for deep learning that helps newcomers and practitioners navigate the vast literature in a structured and intentional way. It is built around several guiding principles: moving from outline to detail, from older foundational papers to state-of-the-art work, and from generic to more specialized areas while keeping a focus on impactful contributions. The roadmap organizes papers into categories such as fundamentals,... -
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mlcourse.ai
Open Machine Learning Course
...Currently, the course is in a self-paced mode. Here we guide you through the self-paced mlcourse.ai. -
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Introduction to Vue.js 3 Course
Workshop Materials for my Introduction to Vue.js Workshop
Introduction to Vue.js 3 Course houses the workshop materials for an “Introduction to Vue.js” course created by Sarah Drasner, originally delivered on Frontend Masters. The content covers essential Vue.js concepts such as directives, data rendering, methods, watchers, computed properties, components, slots, and the Composition API (for Vue 3), complemented with example code and exercises. Since the course was updated for Vue 3, the repo includes directories for both Vue 2 and Vue 3... -
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MoCo v3
PyTorch implementation of MoCo v3
MoCo v3 is a PyTorch reimplementation of Momentum Contrast v3 (MoCo v3), Facebook Research’s state-of-the-art self-supervised learning framework for visual representation learning using ResNet and Vision Transformer (ViT) backbones. Originally developed in TensorFlow for TPUs, this version faithfully reproduces the paper’s results on GPUs while offering an accessible and scalable PyTorch interface. MoCo v3 introduces improvements for training self-supervised ViTs by combining contrastive learning with transformer-based architectures, achieving strong linear and end-to-end fine-tuning performance on ImageNet benchmarks. ... -
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English Grammar Notes
Learn English grammar from 0
English Grammar Notes is a community-driven learning resource project aimed at helping learners master English grammar from the ground up through clear explanations, practice examples, and progressive note structure that breaks down complex rules into accessible segments. The repository combines educational content written in simplified English and Chinese alongside structured markdown pages that cover parts of speech, sentence structure, tenses, clauses, and other core grammar topics, making it useful for both self-study and classroom contexts. ... -
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Deep Learning 500 Questions
500 Questions on Deep Learning using a question-and-answer format
DeepLearning-500-questions is a comprehensive handbook that compiles 500 important questions on deep learning, curated to serve as a valuable reference for AI engineer interviews and self-study. Edited by Tan Jiyong with contributions from Guo Zizhao, Li Jian, and Dian Songyi, the book systematically covers both theoretical foundations and practical applications of deep learning. The first sections focus on essential mathematics, machine learning basics, and deep learning foundations, establishing the groundwork for more advanced topics. ... -
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TensorFlow Examples
TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)
TensorFlow Examples is a comprehensive repository of example implementations, tutorials, and reference code intended to help newcomers and intermediate learners dive into TensorFlow quickly. It contains both Jupyter notebooks and raw source code, covering a broad range of tasks: from basic machine-learning and neural-network models to more advanced use cases, using both TensorFlow v1 and v2 APIs. For clarity and educational value, each example is accompanied by explanatory comments or markdown cells to illustrate what the code does and why — a design that makes it especially suitable for self-learners or students following along with real data. ... -
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Deep-Learning-with-TensorFlow-book
Open source Deep Learning book, based on TensorFlow
...The project also supports educational use, with materials that can be adopted by students, self-learners, and instructors. Overall, it is a complete learning package for understanding modern deep learning workflows through TensorFlow 2.0 examples. -
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python-tutorial
Practical Python tutorials, including Python basics
...Its examples are tested in a Python 3 environment and organized into topic-based directories. The repository also includes notebook-style learning materials for basic data types and core language concepts. It is useful as a structured self-study resource, classroom supplement, or quick reference for practical Python usage. -
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PyTorchVideo
A deep learning library for video understanding research
PyTorchVideo is a deep learning library for video understanding, providing modular components and pretrained models for tasks like action recognition, video classification, detection, and self-supervised learning. It is tightly integrated with PyTorch and PyTorch Lightning, offering flexible APIs for building and training spatiotemporal networks. The library includes efficient implementations of state-of-the-art architectures such as SlowFast, X3D, and MViT, optimized for both research prototyping and production inference. ...
