Search Results for "learn language"
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Showing 340 open source projects for "learn language"
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Ai-Learn
The artificial intelligence learning roadmap compiles 200 cases
Ai-Learn is an open-source artificial intelligence learning roadmap that aggregates educational materials, tutorials, and practical projects designed to help beginners study AI and machine learning systematically. The repository was created to help learners start self-study programs in artificial intelligence without getting overwhelmed by the large number of available resources. -
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Learn Elixir
Learn the Elixir programming language to build functional web apps
learn-elixir is a practical, beginner-friendly guide to learning Elixir and the Erlang VM (BEAM), emphasizing why Elixir scales—lightweight processes, immutable data, robust GC, and supervisors—and how to apply those strengths in real projects. The repo walks you from installation on macOS, Ubuntu, and Windows to an interactive workflow using iex, Livebook, and even a one-line Docker run for a zero-install setup. It teaches Elixir’s core types and syntax with short, runnable examples, then... -
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Learn Go with Tests
Learn Go with test-driven development
Katas are fun but they are usually limited in their scope for learning a language; you're unlikely to use goroutines to solve a kata. Another problem is when you have varying levels of enthusiasm. Some people just learn way more of the language than others and when demonstrating what they have done end up confusing people with features the others are not familiar with. This ends up making the learning feel quite unstructured and ad hoc. -
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Learn Go
Master the fundamentals and advanced features of the Go language
Learn Go is a learning-focused repository built to teach Go from first principles through more advanced language and ecosystem features. It takes a course-like approach, starting with environment setup and the “Hello world” basics, then moving into variables, types, formatting, control flow, and functions. From there, it expands into Go’s practical structure for real projects, including modules, packages, and workspaces, plus useful commands for building and working with programs. ... -
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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. It mixes courses, articles, code labs, and videos, emphasizing materials that teach both concepts... -
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The Futhark Programming Language
A data-parallel functional programming language
Futhark is a small programming language designed to be compiled into efficient parallel code. It is a statically typed, data-parallel, and purely functional array language in the ML family, and comes with a heavily optimizing ahead-of-time compiler that presently generates either GPU code via CUDA and OpenCL, or multi-threaded CPU code. Futhark is not designed for graphics programming, but can instead use the compute power of the GPU to accelerate data-parallel array computations. The... -
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V Programming Language
Simple, fast, safe, compiled language for developing software
Simple language for building maintainable programs. You can learn the entire language by going through the documentation over a weekend, and in most cases, there's only one way to do something. This results in simple, readable, and maintainable code. Despite being simple, V gives a lot of power to the developer and can be used in pretty much every field, including systems programming, webdev, gamedev, GUI, mobile, science, embedded, tooling, etc. -
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Roadmap To Learn Generative AI In 2025
Basic Machine Learning Natural Language Processing Roadmap
Roadmap To Learn Generative AI In 2025 is a curated learning path focused on contemporary generative AI — covering large language models (LLMs), diffusion-based image generation, prompt engineering, multi-modal AI, fine-tuning techniques, and the practical considerations for deploying generative models. It’s aimed at learners and developers who already have some programming or ML basics and wish to specialize in generative AI, offering a modern, structured plan that reflects the state of the art as of 2025. ... -
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GDevelop
The game engine for everyone
GDevelop is an open-source, cross-platform game development software designed to make creating HTML5 and native games easy for everyone. Experts and novices alike can create their own games with GDevelop as it is fast and easy to learn, requiring no knowledge in a specific programming language. What makes GDevelop unique and so easy to use is its powerful and intuitive event-based system. Events are a powerful way to build up your game logic, without having to learn a programming language. GDevelop also features ready-made behaviors for your game objects, and allows you to create new behaviors through the easy to learn events. ... -
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Tidal
Pattern language
...By default, sound is made with the featureful SuperDirt synth/sampler, but you can control other synths using Open Sound Control (OSC) or MIDI. Whether you're using SuperDirt or a synth, every filter and effect can be manipulated independently with Tidal patterns. Tidal is embedded in the Haskell language, although you don't have to learn Haskell to learn Tidal. You can learn Tidal through experimentation and play, most Tidal coders have little or no experience in software engineering. -
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Scikit-LLM
Seamlessly integrate LLMs into scikit-learn
Seamlessly integrate powerful language models like ChatGPT into sci-kit-learn for enhanced text analysis tasks. At the moment the majority of the Scikit-LLM estimators are only compatible with some of the OpenAI models. Hence, a user-provided OpenAI API key is required. Additionally, Scikit-LLM will ensure that the obtained response contains a valid label. If this is not the case, a label will be selected randomly (label probabilities are proportional to label occurrences in the training set). ... -
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FinGLM
Committed to building an open, public welfare
FinGLM is an open-source financial large language model initiative aimed at advancing artificial intelligence applications within the finance industry. The project focuses on developing domain-specific language models that understand financial terminology, corporate reports, and economic datasets. By combining large language model architectures with financial datasets such as corporate annual reports and structured financial records, FinGLM aims to improve AI performance on tasks that require domain expertise. ... -
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Lingua-Py
The most accurate natural language detection library for Python
Language detection is often done as part of large machine learning frameworks or natural language processing applications. In cases where you don't need the full-fledged functionality of those systems or don't want to learn the ropes of those, a small flexible library comes in handy. -
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Baby Buddy
Helps caregivers track sleep, feedings, diaper changes, and tummy time
Language can be set on a per-user basis from the user settings page (/user/settings/). -
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TextWorld
TextWorld is a sandbox learning environment for the training
TextWorld is a learning environment designed to train reinforcement learning agents to play text-based games, where actions and observations are entirely in natural language. Developed by Microsoft Research, TextWorld focuses on language understanding, planning, and interaction in complex, narrative-driven environments. It generates games procedurally, enabling scalable testing of agents’ natural language processing and decision-making abilities. -
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Prompt in-context learning
Resources for in-context learning and prompt engineering
Prompt-In-Context-Learning is an open-source repository that serves as a comprehensive engineering guide and curated resource collection for understanding and applying in-context learning and prompt engineering with large language models. The project gathers research papers, tutorials, prompt examples, and practical guides that help developers and researchers learn how to design effective prompts for models such as GPT-3, ChatGPT, and other foundation models. In-context learning refers to the ability of language models to learn a task directly from examples provided in the prompt without updating the model’s parameters, allowing them to perform new tasks through demonstration alone. ... -
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Read Frog
Open Source Immersive Translate
Read Frog is an open-source browser extension designed to transform everyday web reading into an immersive language learning experience powered by artificial intelligence. The tool integrates translation, contextual explanations, and content analysis directly into the browsing workflow so users can learn languages naturally while reading authentic online content. Instead of forcing learners to switch between translation tools and the original text, the extension displays translations alongside the source language, making comprehension immediate and continuous. ... -
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query-json
Faster, simpler and more portable implementation of `jq` in Reason
query-json is a faster, simpler, and more portable implementation of the jq language in Reason distributed as a dependency-free binary thanks to the OCaml compiler, and distributed to the web with js_of_ocaml. query-json allows you to write small programs to operate on top of json files with a concise syntax. Learn how to write a Programming Language with the OCaml stack using menhir and select with great error messages. -
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JuMP
Modeling language for Mathematical Optimization
JuMP is a modeling language and collection of supporting packages for mathematical optimization in Julia. JuMP makes it easy to formulate and solve a range of problem classes, including linear programs, integer programs, conic programs, semidefinite programs, and constrained nonlinear programs. JuMP is used to solve large-scale inventory routing problems at Renault, schedule trains at Thales Inc., plan power grid expansion at PSR, and route school buses. -
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InternVL
A Pioneering Open-Source Alternative to GPT-4o
InternVL is a large-scale multimodal foundation model designed to integrate computer vision and language understanding within a unified architecture. The project focuses on scaling vision models and aligning them with large language models so that they can perform tasks involving both visual and textual information. InternVL is trained on massive collections of image-text data, enabling it to learn representations that capture both visual patterns and semantic meaning. ... -
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LLaMA-Mesh
Unifying 3D Mesh Generation with Language Models
...The project includes a supervised fine-tuning dataset composed of interleaved text and mesh data, allowing the model to learn relationships between textual descriptions and 3D structures. As a result, the model can generate mesh models directly from text prompts, explain mesh structures in natural language, or output mixed text-and-mesh sequences. This unified representation enables a single model to operate across both textual and spatial domains. -
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vyper
Pythonic Smart Contract Language for the EVM
See Installing Vyper to install vyper. See Tools and Resources for an additional list of framework and tools with vyper support. See Documentation for the documentation and overall design goals of the Vyper language. See Learn.Vyperlang.org for learning Vyper by building a Pokémon game. See try.vyperlang.org to use Vyper in a hosted jupyter environment! There is also an online compiler available you can use to experiment with the language and compile to bytecode and/or IR. While the vyper... -
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Agentic Context Engine
Make your agents learn from experience
Agentic Context Engine (ACE) is an open-source framework designed to help AI agents improve their performance by learning from their own execution history. Instead of relying solely on model training or fine-tuning, the framework focuses on structured context engineering, allowing agents to accumulate knowledge from past successes and failures during task execution. The system treats context as a dynamic “playbook” that evolves over time through a process of generation, reflection, and... -
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DriveLM
Driving with Graph Visual Question Answering
...The system includes DriveLM-Data, a dataset built on driving environments such as nuScenes and CARLA, where human-written reasoning steps connect different layers of driving tasks. This design allows models to learn relationships between objects, behaviors, and navigation decisions through graph-structured logic. -
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handy-ollama
Implement CPU from scratch and play with large model deployments
handy-ollama is an open-source educational project designed to help developers and AI enthusiasts learn how to deploy and run large language models locally using the Ollama platform. The repository serves as a structured tutorial that explains how to install, configure, and use Ollama to run modern language models on personal hardware without requiring advanced infrastructure. A key focus of the project is enabling users to run large models even without GPUs by leveraging optimized CPU-based inference pipelines. ...
