Search Results for "learning" - Page 23
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Showing 4193 open source projects for "learning"
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$300 Free Credits for Your Google Cloud ProjectsLaunch your next project with $300 in free Google Cloud credits—no strings attached. Test, build, and deploy without risk. Use your credits across the entire Google Cloud platform to find what works best for your needs. After your credits are used, continue with always-free tier services. Only pay when you're ready to scale. Sign up in minutes and start exploring.
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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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txtai
Build AI-powered semantic search applications
txtai executes machine-learning workflows to transform data and build AI-powered semantic search applications. Traditional search systems use keywords to find data. Semantic search applications have an understanding of natural language and identify results that have the same meaning, not necessarily the same keywords. Backed by state-of-the-art machine learning models, data is transformed into vector representations for search (also known as embeddings). -
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DevOps Roadmap 2026
DevOps Roadmap for 2026. with learning resources
DevOps Roadmap is a structured 2026 learning guide for people preparing for DevOps engineering roles. It presents the field as a sequence of practical competencies rather than a list of fashionable products. The path begins with Git, a programming language, Linux, scripting, networking, security, and server administration. It then advances through containers, Kubernetes, infrastructure as code, CI/CD, monitoring, observability, cloud platforms, and software engineering practices. ... -
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Grid Garden
A game for learning CSS grid layout
Grid Garden is an interactive browser game for learning CSS Grid layout. It teaches Grid concepts by asking players to water carrots and avoid weeds using CSS grid properties. The game makes grid placement, sizing, and alignment feel concrete through visual levels instead of static documentation. Learners practice properties such as grid-column-start, grid-column-end, grid-row-start, grid-row-end, grid-template-columns, grid-template-rows, and order. -
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IntelliJ-IDEA-Tutorial
Tutorial repository focused on teaching IntelliJ IDEA
...The guide supports multiple versions of IntelliJ IDEA and also includes related JetBrains tools such as WebStorm, PhpStorm, PyCharm, RubyMine, Android Studio, CLion, GoLand, and DataGrip. It is structured as a learning resource for both beginners and users who want to improve productivity inside JetBrains IDEs. The project includes many separate markdown chapters, images, and reference sections. It is especially useful for Chinese-speaking developers learning professional Java and IDE workflows. -
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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Swift Macros
A curated list of awesome Swift Macros
...It is especially valuable for developers moving from code-generation tools toward Swift’s built-in macro system. Swift-Macros is not a single library, but a reference hub for learning the Swift macro ecosystem and finding useful implementation patterns. -
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Hacking with Swift
The project source code for Hacking with iOS
...It contains a large collection of example projects, exercises, and complete applications that guide learners from beginner to advanced levels. The repository is structured into different learning tracks, including UIKit-based development and modern SwiftUI approaches, allowing developers to explore multiple paradigms within the Apple ecosystem. Each project is designed to reinforce specific concepts such as UI design, data handling, animations, and app architecture. The material emphasizes hands-on learning, encouraging users to build real applications rather than passively consume theory. ... -
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Vibe Vibe
The First Systematic Vibe Coding Tutorial
...The repository is organized into multiple learning stages, including foundational concepts, advanced techniques, and hands-on projects that reinforce practical skills. It also includes deployment instructions and optional local hosting through Docker, making the platform accessible in both online and offline environments. -
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mosaicml composer
Supercharge Your Model Training
composer is a deep learning training framework built on PyTorch and designed to make large-scale model training more efficient, scalable, and customizable. At the center of the project is a highly optimized Trainer abstraction that simplifies the management of training loops, parallelization, metrics, logging, and data loading. The framework is intended for modern workloads that may span anything from a single GPU to very large distributed training environments, which makes it suitable for both experimentation and production-scale development. ... -
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Useful Java links
A list of useful Java frameworks, libraries, software and hello worlds
...These resources cover many areas of software development, including web frameworks, testing libraries, concurrency tools, build systems, microservices architectures, and development best practices. By grouping links into categorized sections, the repository allows developers to quickly discover relevant technologies and learning materials for building Java applications. The project is maintained as a living reference library that evolves alongside the Java ecosystem as new frameworks and development tools emerge. -
Build Securely on AWS with Proven FrameworksMoving to the cloud brings new challenges. How can you manage a larger attack surface while ensuring great network performance? Turn to Fortinet’s Tested Reference Architectures, blueprints for designing and securing cloud environments built by cybersecurity experts. Learn more and explore use cases in this white paper.
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llm_interview_note
Mainly record the knowledge and interview questions
...The repository also explores practical engineering concerns including distributed training strategies, dataset construction, model parameters, and scaling techniques used in large-scale machine learning systems. By organizing topics in a hierarchical documentation format, it enables readers to progress from basic NLP concepts to advanced topics like mixture-of-experts architectures and large-scale training frameworks. -
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vim-be-good
nvim plugin designed to make you better at Vim Movements
vim-be-good is a fun, game-oriented Neovim plugin developed by ThePrimeagen that turns learning and practicing Vim movement commands into an interactive experience. Rather than merely memorizing keystrokes, users play engaging mini-games inside Neovim where they must use proper movement commands (like jumping, searching, and editing) to complete challenges, making skill development more enjoyable and practice less repetitive. -
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AI-Job-Notes
AI algorithm position job search strategy
AI-Job-Notes is a pragmatic notebook for landing roles in machine learning, computer vision, and related engineering tracks. It assembles study paths, checklists, and interview prep materials, but also covers job-search mechanics—portfolio building, resume patterns, and communication tips. The emphasis is on doing: practicing with project ideas, setting up reproducible experiments, and showcasing results that convey impact. -
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TorchDistill
A coding-free framework built on PyTorch
...Even when you need to extract intermediate representations in teacher/student models, you will NOT need to reimplement the models, which often change the interface of the forward, but instead specify the module path(s) in the yaml file. In addition to knowledge distillation, this framework helps you design and perform general deep learning experiments (WITHOUT coding) for reproducible deep learning studies. i.e., it enables you to train models without teachers simply by excluding teacher entries from a declarative yaml config file. -
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Haiku Sonnet for JAX
JAX-based neural network library
Haiku is a library built on top of JAX designed to provide simple, composable abstractions for machine learning research. JAX is a numerical computing library that combines NumPy, automatic differentiation, and first-class GPU/TPU support. Haiku is a simple neural network library for JAX that enables users to use familiar object-oriented programming models while allowing full access to JAX's pure function transformations. Haiku provides two core tools: a module abstraction, hk.Module, and a simple function transformation, hk.transform. hk.Modules are Python objects that hold references to their own parameters, other modules, and methods that apply functions on user inputs. hk.transform turns functions that use these object-oriented, functionally "impure" modules into pure functions that can be used with jax.jit, jax.grad, jax.pmap, etc. -
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Flux.jl
Relax! Flux is the ML library that doesn't make you tensor
Flux is an elegant approach to machine learning. It's a 100% pure Julia stack and provides lightweight abstractions on top of Julia's native GPU and AD support. Flux makes the easy things easy while remaining fully hackable. Flux provides a single, intuitive way to define models, just like mathematical notation. Julia transparently compiles your code, optimizing and fusing kernels for the GPU, for the best performance. -
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MLRun
Machine Learning automation and tracking
MLRun is an open MLOps framework for quickly building and managing continuous ML and generative AI applications across their lifecycle. MLRun integrates into your development and CI/CD environment and automates the delivery of production data, ML pipelines, and online applications, significantly reducing engineering efforts, time to production, and computation resources. MLRun breaks the silos between data, ML, software, and DevOps/MLOps teams, enabling collaboration and fast continuous... -
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AWESOME DATA SCIENCE
Awesome Data Science repository to learn and apply for real world
An open source Data Science repository to learn and apply towards solving real world problems. This is a shortcut path to start studying Data Science. Just follow the steps to answer the questions, "What is Data Science and what should I study to learn Data Science?" Data Science is one of the hottest topics on the Computer and Internet farmland nowadays. People have gathered data from applications and systems until today and now is the time to analyze them. The next steps are producing... -
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Artificial Intelligence for Beginners
12 Weeks, 24 Lessons, AI for All
...The curriculum is intentionally beginner-friendly while still exposing learners to widely used frameworks such as TensorFlow and PyTorch. It also supports many languages, making the material accessible to a global audience. Overall, the project functions as a complete self-paced learning pathway for students, educators, and developers who want a practical introduction to modern AI concepts. -
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age
A simple, modern and secure encryption tool (and Go library)
...Because of its design philosophy, it avoids the bloat of many older encryption utilities while maintaining strong cryptographic hygiene. It’s especially useful for developers or system administrators who want to adopt encryption without learning a multitude of options. -
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33 JS Concepts
33 JavaScript concepts every developer should know
33-js-concepts is a curated collection of essential JavaScript concepts that every developer should understand to strengthen their knowledge of the language. The project was originally inspired by an article by Stephen Curtis and has since grown into a community-driven learning resource. It serves as a roadmap for developers to review and master core principles such as closures, promises, prototypes, event loops, and other critical topics. While not a strict curriculum, it provides a structured path for deeper study and practical learning. The repository also encourages contributions, including personal notes, recaps, and translations, making it accessible to developers worldwide. ... -
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Lance
Modern columnar data format for ML and LLMs implemented in Rust
Lance is a columnar data format that is easy and fast to version, query and train on. It’s designed to be used with images, videos, 3D point clouds, audio and of course tabular data. It supports any POSIX file systems, and cloud storage like AWS S3 and Google Cloud Storage. -
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gensim
Topic Modelling for Humans
Gensim is a Python library for topic modeling, document indexing, and similarity retrieval with large corpora. The target audience is the natural language processing (NLP) and information retrieval (IR) community. -
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Roadmap To Learn Generative AI In 2025
Basic Machine Learning Natural Language Processing Roadmap
...The roadmap outlines recommended topics, sequential steps, and associated resources (tutorials, notebooks, project ideas) to build competence in generative modeling from conceptual understanding to implementation and deployment. By organizing the learning journey in digestible phases — from fundamentals of neural networks to deep generative architectures, and from model training to serving/inference pipelines — it reduces the cognitive load of “where to start”. -
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Learn AI Engineering
Learn AI and LLMs from scratch using free resources
Learn AI Engineering is a learning path for AI engineering that consolidates high-quality, free resources across the full stack: math, Python foundations, machine learning, deep learning, LLMs, agents, tooling, and deployment. Rather than a loose bookmark list, it organizes topics into a progression so learners can start from fundamentals and move toward practical, production-oriented skills. -
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Kedro
A Python framework for creating reproducible, maintainable code
...Puts the "engineering" back into data science because it borrows concepts from software engineering and applies them to machine-learning code. It is the foundation for clean, data science code.