Search Results for "programming languages learning" - Page 7
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Showing 1291 open source projects for "programming languages learning"
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CodeGen
Open-source model for program synthesis
CodeGen is a family of open-source large language models designed specifically for program synthesis and code generation tasks. Developed by Salesforce Research, the models are trained on large datasets containing both natural language and programming language content. This allows them to translate natural language descriptions into functional code across a variety of programming languages. CodeGen supports multi-turn program synthesis, meaning it can generate complex programs through a sequence of prompts that progressively refine the solution. The project also includes training infrastructure and model checkpoints that allow researchers to experiment with different model sizes and training configurations. ... -
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Pkl
A configuration as code language with rich validation and tooling
pkl is a purpose-built configuration-as-code language developed by Apple that combines declarative structure, validation, and tooling to improve over traditional configuration formats like JSON, YAML, or Plists. Its goal is to let you write configuration logic (modules, imports, conditions, defaults) while still producing static outputs suitable for tools that expect JSON, YAML, or other formats. Configurations in Pkl are type-safe and support validation constraints (e.g. bounds, relations)... -
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SpinalHDL
Scala based HDL
SpinalHDL is a hardware description (HDL) framework embedded in Scala, enabling hardware designers to build digital circuits with modern programming abstractions. Instead of writing in Verilog or VHDL directly, users describe hardware components and their interconnects using Scala code and Spinal’s domain-specific library, which then emits synthesizable hardware (e.g. as Verilog). Because SpinalHDL is embedded in Scala, it allows reuse of functional abstractions, parameterization, modular... -
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Jittor
Jittor is a high-performance deep learning framework
...The front-end language is Python. Module Design and Dynamic Graph Execution is used in the front-end, which is the most popular design for deep learning framework interface. The back-end is implemented by high-performance languages, such as CUDA, C++. Jittor'op is similar to NumPy. Let's try some operations. We create Var a and b via operation jt.float32, and add them. Printing those variables shows they have the same shape and dtype. -
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Games on GitHub
A list of games, add-ons, maps, etc. hosted on GitHub
...The repository is organized by categories such as browser-based games, native games, mobile games, chat bots, source-only projects, frameworks, engines, libraries, plugins, utilities, and related resources. It includes projects across many genres, platforms, engines, and programming languages. Because the repository is now archived and read-only, it is best treated as a historical discovery list rather than an actively maintained catalog. Overall, it remains useful for exploring open-source game development examples, older community projects, and game-related technical resources. -
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Devicon
Set of icons representing programming languages, design & development
Devicon is a set of icons representing programming languages, designing, and development tools. You can use it as a font or directly copy/paste the SVG code into your project. Devicon aims to gather all logos representing development languages and tools. Each icon comes in several versions: font/SVG, original/plain/line, colored/not colored, wordmark/no wordmark. Devicon has 150+ icons. -
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raylib
A simple and easy-to-use library to enjoy videogames programming
raylib is highly inspired by Borland BGI graphics lib and by XNA framework. Do you want to see all functions available in raylib? Check raylib cheatsheet. raylib is a programming library to enjoy videogames programming; no fancy interface, no visual helpers, no auto-debugging, just coding in the most pure spartan-programmers way. raylib has received several recognitions in the last years and many people have written about the library. Here there are the main awards received from Google and... -
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Computational Thinking
Introduction to computational thinking with Julia
Computational Thinking is an open source MIT course repository that teaches computational problem-solving through the Julia programming language. The course integrates mathematics, computing, and real-world applications into a unified curriculum, making it suitable for students across science, engineering, and data-driven fields. It emphasizes learning how to translate problems into computational terms and developing algorithms and models to analyze them effectively. -
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Thinc
A refreshing functional take on deep learning
Thinc is a lightweight deep learning library that offers an elegant, type-checked, functional-programming API for composing models, with support for layers defined in other frameworks such as PyTorch, TensorFlow and MXNet. You can use Thinc as an interface layer, a standalone toolkit or a flexible way to develop new models. Previous versions of Thinc have been running quietly in production in thousands of companies, via both spaCy and Prodigy. -
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.NET Core Home
Home repository for .NET Core
This is the dotnet/core repository and is a good starting point for .NET Core, an open source general-purpose development framework for building cross-platform apps. .NET Core lets you create apps for Windows, macOS or Linux, as well as ARM64 processors using various programming languages. It provides frameworks and APIs for cloud, client UI, IoT, and machine learning. The latest major release (as of this writing) is .NET Core 3.1. You must be on the latest patch release in order to get support from Microsoft. -
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mruby
Lightweight Ruby
mruby is a lightweight implementation of the Ruby programming language designed for embedding and integration into applications, particularly in resource-constrained environments such as embedded systems or game engines. It maintains compatibility with modern Ruby syntax while offering a significantly reduced footprint compared to the standard Ruby interpreter. The system includes its own virtual machine, bytecode compiler, and interactive shell, enabling developers to write, compile, and... -
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Basic Computer Games
An updated version of the classic "Basic Computer Games" book
Basic Computer Games is a modern revitalization of the classic “Basic Computer Games” book’s collection of games, ported and expanded into various modern, memory-safe and scripting languages. It includes illustrative code examples of many classic games (e.g. Blackjack, Bowling) in multiple languages, with the goal of making the historical games accessible and educational in safe modern environments. Definitely use the most recent versions and features of the target language, but also try to keep the code samples simple and explainable – the goal is to teach programming in the target language, not necessarily demonstrate the cleverest one-line tricks, or big system "enterprise" coding techniques designed for thousands of lines of code. -
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Microsoft Kiota
OpenAPI based HTTP Client code generator
Microsoft Kiota is an open-source tool that generates client libraries from OpenAPI descriptions, making it easier to interact with RESTful APIs. It is designed to work seamlessly with Microsoft Graph and other API ecosystems, providing strongly typed SDKs in multiple programming languages. Kiota simplifies API consumption by automating the creation of client libraries, reducing the manual effort needed to integrate with APIs. -
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Liger Kernel
Efficient Triton Kernels for LLM Training
Liger Kernel is a unified kernel developed by LinkedIn to streamline data science and machine learning workflows across different languages and tools. It provides a consistent interface for running code in various languages (such as Python, R, SQL) within a single Jupyter-like environment, enhancing productivity and collaboration for data scientists working in mixed-language projects. -
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GitHub Trending Repos
Track GitHub trending repositories in your favorite programming lang
GitHub Trending Repos is a notification service for tracking repositories that appear on GitHub Trending. It organizes subscriptions by programming language through dedicated GitHub issues. A scheduled script retrieves trending repositories and posts new results as comments to the corresponding issues. Subscribers then receive the updates through GitHub notifications or email. Users can choose daily or weekly schedules for many supported languages. The project covers a broad range of ecosystems, including JavaScript, Python, Go, Rust, Java, TypeScript, C++, and many others. -
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TensorFlow Quantum
Open-source Python framework for hybrid quantum-classical ml learning
TensorFlow Quantum is an open-source software framework designed for building and training hybrid quantum-classical machine learning models within the TensorFlow ecosystem. The framework enables researchers and developers to represent quantum circuits as data and integrate them directly into machine learning workflows. By combining classical deep learning techniques with quantum algorithms, the platform allows experimentation with quantum machine learning methods that may offer advantages... -
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ispc
Intel SPMD Program Compiler
ispc is a compiler for a variant of the C programming language, with extensions for single programs, and multiple data programming. Under the SPMD model, the programmer writes a program that generally appears to be a regular serial program, though the execution model is actually that a number of program instances execute in parallel on the hardware. ispc compiles a C-based SPMD programming language to run on the SIMD units of CPUs and GPUs; it frequently provides a 3x or more speedup on... -
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Flower
Flower: A Friendly Federated Learning Framework
A unified approach to federated learning, analytics, and evaluation. Federate any workload, any ML framework, and any programming language. Federated learning systems vary wildly from one use case to another. Flower allows for a wide range of different configurations depending on the needs of each individual use case. Flower originated from a research project at the University of Oxford, so it was built with AI research in mind. -
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cheat.sh
The only cheat sheet you need
cheat.sh is a compact, network-accessible cheat-sheet service that serves concise examples and usage notes for hundreds of shell commands, programming languages, and tools via a simple HTTP interface. You can query it from the terminal (for example curl cht.sh/rsync or curl cheat.sh/ls) or browse the web front page; it also supports a shorthand hostname (cht.sh) and provides both online and standalone/local installation modes. The repository contains the server and client code, instructions to run a local standalone instance (including Python virtualenv setup), and tooling to fetch or maintain the upstream cheat-sheet data; installation documentation explains disk-space needs and dependency setup for offline use. ... -
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Fanyi
A 🇨🇳 and 🇺🇸 translate tool in your command line
Fanyi is a tool for translating words between the Chinese and English languages, right in your command line. It’s a good supportive tool for learning and reading the Chinese language from English, or the other way around. All translation data is fetched from iciba.com and fanyi.youdao.com, and with each translation comprehensive and related samples are given for better understanding and proper usage. There are translations for words as well as sentences, and in Mac/Linux bash, words can even be pronounced by the ‘say’ command. -
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BAML
The AI framework that adds the engineering to prompt engineering
...This design allows developers to treat language model interactions as predictable software components rather than ad-hoc prompt strings. The framework enables developers to define prompt logic in a dedicated language while integrating it into applications written in various programming languages such as Python, TypeScript, Ruby, and Go. BAML also allows developers to specify which models are used for each prompt and how outputs should be validated or structured. By converting prompt engineering into a more formal programming workflow, the framework improves reliability, debugging, and maintainability of AI systems. -
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MiMo-V2.5-ASR
Robust Speech Recognition Across Languages, Dialects
MiMo-V2.5-ASR is an advanced automatic speech recognition system developed as part of Xiaomi’s MiMo AI ecosystem. It is designed to handle complex acoustic environments, including noisy conditions and diverse speaker variations. The model supports multiple languages and dialects, enabling robust transcription across global use cases. It leverages modern deep learning architectures to improve accuracy and adaptability in real-world scenarios. The system is built to integrate with broader AI pipelines, including voice assistants and multimodal systems. It focuses on scalability and performance, making it suitable for both research and production applications. ... -
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cuML
RAPIDS Machine Learning Library
cuML is a suite of libraries that implement machine learning algorithms and mathematical primitives functions that share compatible APIs with other RAPIDS projects. cuML enables data scientists, researchers, and software engineers to run traditional tabular ML tasks on GPUs without going into the details of CUDA programming. In most cases, cuML's Python API matches the API from scikit-learn. -
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Bend
A massively parallel, high-level programming language
Bend is an interactive programming environment (REPL) built on top of the Kotlin language, designed to allow users to explore, experiment, and learn Kotlin in a live, feedback-driven manner. The tool lets you define variables, functions, or values at the prompt and iteratively refine them—immediately seeing output and types—while preserving state across commands. It emphasizes discoverability and experimentation: users can inspect functions, call them on sample inputs, and evolve logic... -
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DevDocs
API Documentation Browser
The devdocs repository powers the DevDocs web application, a fast, offline-friendly documentation browser for many programming languages, libraries, and APIs. It aggregates documentation from multiple sources (e.g., MDN, Python, Ruby, Git, etc.), converts them into a uniform format, and indexes them for instant text searching. The codebase includes a backend that handles ingestion, parsing, and transformation of documentation sources into a static site structure, as well as the client side UI code for browsing, searching, and reading docs in a responsive interface. ...
