Search Results for "programming learning system"
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Showing 192 open source projects for "programming learning system"
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Professional Programming
A collection of learning resources for curious software engineers
Professional Programming is a long-running, curated collection of learning resources aimed at helping software engineers grow into well-rounded professionals. It goes far beyond basic “learn to code” material and covers topics like system design, debugging, testing, performance, security, architecture, and software craftsmanship. The list is organized by themes such as coding, design, operations, communication, and career, making it easy to dive into specific aspects of engineering practice. ... -
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Python-programming-exercises
100+ Python challenging programming exercises
Python-programming-exercises is an educational repository containing more than 100 Python programming challenges. It is designed to help learners practice problem solving through short exercises rather than full applications. The exercises cover fundamentals such as strings, numbers, loops, lists, dictionaries, functions, regular expressions, file handling, classes, generators, and algorithmic thinking. Many problems include both a prompt and a suggested solution, making the repository... -
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Rust Programming Language
Empowering everyone to build reliable and efficient software
The Rust Programming Language is a language that empowers you to build reliable and efficient software. It runs blazingly fast and is memory-efficient, so it can power performance-critical services and run on embedded devices. It has a rich type system and ownership model, ensuring both thread and memory safety. Consisting of a standard library, great documentation and a friendly compiler, plus a top-notch build tool, package manager, auto-formatter and many other great tools, it’s the language of choice for increased productivity. ... -
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GoBooks
List of Golang books
GoBooks is a curated collection of recommended books and learning resources for the Go programming language. It serves developers ranging from complete beginners to experienced engineers working with concurrency, performance, web development, and system design. The repository organizes titles into popular, starter, advanced, and web development categories. Each entry includes useful context such as publication date, author, format, and a short description. -
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A to Z Resources for Students
Curated list of resources for developers
A to Z Resources for Students is a curated directory of learning materials, developer tools, programs, events, and career opportunities for students and early-career technologists. It helps users discover resources for learning programming languages, frameworks, AI, machine learning, cybersecurity, mobile development, and other technical fields. The collection also includes hackathons, competitions, internships, student programs, open-source opportunities, and networking communities. ... -
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toBeBetterJavaer
An easy-to-understand and humorous Java study guide
toBeBetterJavaer is an extensive Java learning knowledge base designed to help developers progress from fundamentals to professional development topics. It combines original tutorials, learning roadmaps, reference material, and job-interview preparation in one organized repository. Core lessons cover syntax, object-oriented programming, collections, exceptions, I/O, networking, NIO, and modern Java features. -
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TensorFlow.js
TensorFlow.js is a library for machine learning in JavaScript
...Tensors are the core datastructure of TensorFlow.js They are a generalization of vectors and matrices to potentially higher dimensions. Built on top of TensorFlow.js, the ml5.js library provides access to machine learning algorithms and models in the browser with a concise, approachable API. Comfortable with concepts like Tensors, Layers, Optimizers and Loss Functions (or willing to get comfortable with them)? TensorFlow.js provides flexible building blocks for neural network programming in JavaScript. -
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sectorlisp
Bootstrapping LISP in a Boot Sector
The sectorlisp project is a minimal implementation of the Lisp programming language designed to fit within extremely constrained environments. It is engineered to run in very small memory footprints, making it suitable for educational purposes and experimentation with low-level programming concepts. The project demonstrates how a functional programming language can be implemented with minimal resources while still retaining core features. -
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TensorRT
C++ library for high performance inference on NVIDIA GPUs
NVIDIA® TensorRT™ is an SDK for high-performance deep learning inference. It includes a deep learning inference optimizer and runtime that delivers low latency and high throughput for deep learning inference applications. TensorRT-based applications perform up to 40X faster than CPU-only platforms during inference. With TensorRT, you can optimize neural network models trained in all major frameworks, calibrate for lower precision with high accuracy, and deploy to hyperscale data centers, embedded, or automotive product platforms. ... -
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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pytudes
Python programs, usually short, of considerable difficulty
...Many examples emphasize clarity and compactness rather than framework-heavy engineering. pytudes is best understood as a learning library, a coding style reference, and a set of practical programming studies. -
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CodeGuide
This repository is a collection of the author, Xiao Fuge
...It also functions as a guide for both junior developers who want to grow into architects and experienced engineers who seek deeper mastery of system design. By combining educational material with hands-on examples, CodeGuide bridges the gap between theoretical learning and practical application in enterprise-level Java development. -
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Haiku
JAX-based neural network library
Haiku is a library built on top of JAX designed to provide simple, composable abstractions for machine learning research. 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 is designed to make the common things we do such as managing model parameters and other model state simpler and similar in spirit to the Sonnet library that has been widely used across DeepMind. ... -
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MLX42
Codam's own fixed, functioning alternative of the miniLibX
MLX42 is a modern C graphics and windowing library built on top of GLFW and inspired by the original MLX library used in 42 school projects. It aims to provide a higher-level, beginner-friendly abstraction for students learning about graphical programming, while also embracing modern practices like event-driven input, texture rendering, and transparency. MLX42 is structured to reduce boilerplate and simplify the creation of games or interactive applications in C, making it an excellent learning and teaching tool for graphics programming fundamentals. -
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PennyLane
A cross-platform Python library for differentiable programming
A cross-platform Python library for differentiable programming of quantum computers. Train a quantum computer the same way as a neural network. Built-in automatic differentiation of quantum circuits, using the near-term quantum devices directly. You can combine multiple quantum devices with classical processing arbitrarily! Support for hybrid quantum and classical models, and compatible with existing machine learning libraries. -
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HelloGitHub
Share interesting, entry-level open source projects on GitHub
HelloGitHub shares interesting, entry-level open source projects on GitHub. It is updated and released in the form of a monthly magazine on the 28th of every month. The content includes interesting, entry-level open-source projects, open-source books, practical projects, enterprise-level projects, etc., so that you can feel the charm of open source in a short time and fall in love with open source! At first, I just wanted to collect interesting, high-quality, and easy-to-use projects that I... -
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XGBoost
Scalable and Flexible Gradient Boosting
XGBoost is an optimized distributed gradient boosting library, designed to be scalable, flexible, portable and highly efficient. It supports regression, classification, ranking and user defined objectives, and runs on all major operating systems and cloud platforms. XGBoost works by implementing machine learning algorithms under the Gradient Boosting framework. It also offers parallel tree boosting (GBDT, GBRT or GBM) that can quickly and accurately solve many data science problems.... -
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Hacking with Swift
The project source code for Hacking with iOS
HackingWithSwift is an extensive open-source repository that accompanies a popular tutorial series focused on teaching Swift programming for iOS development. 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. ... -
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CPlusPlusThings
Collection of various C++ code samples, utilities, patterns
CPlusPlusThings is a repository collecting various C++ code samples, utilities, patterns, and small example projects. It is less a polished product and more a learning/reference collection of snippets and usages of C++ idioms, data structures, algorithms, utilities, and perhaps tricks or meta-programming exercises. (No prominent README or detailed docs were available from my quick search.) Example implementations of data structures and algorithms. Organized as a learning repository (rather than a production framework). ... -
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OCaml
The core OCaml system: compilers, runtime system, base libraries
OCaml is a general-purpose, industrial-strength programming language with an emphasis on expressiveness and safety. OCaml’s powerful type system means more bugs are caught at compile-time, and large, complex codebases are easier to maintain. This makes it a good language for running critical code. At the same time, sophisticated inference makes the type system unobtrusive, creating a smooth developer experience. -
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PyG
Graph Neural Network Library for PyTorch
PyG (PyTorch Geometric) is a library built upon PyTorch to easily write and train Graph Neural Networks (GNNs) for a wide range of applications related to structured data. It consists of various methods for deep learning on graphs and other irregular structures, also known as geometric deep learning, from a variety of published papers. In addition, it consists of easy-to-use mini-batch loaders for operating on many small and single giant graphs, multi GPU-support, DataPipe support,... -
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PyTorch Geometric
Geometric deep learning extension library for PyTorch
It consists of various methods for deep learning on graphs and other irregular structures, also known as geometric deep learning, from a variety of published papers. In addition, it consists of an easy-to-use mini-batch loader for many small and single giant graphs, a large number of common benchmark datasets (based on simple interfaces to create your own), and helpful transforms, both for learning on arbitrary graphs as well as on 3D meshes or point clouds. -
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mlpack
mlpack: a scalable C++ machine learning library
mlpack is an intuitive, fast, and flexible C++ machine learning library with bindings to other languages. It is meant to be a machine learning analog to LAPACK, and aims to implement a wide array of machine learning methods and functions as a "swiss army knife" for machine learning researchers. In addition to its powerful C++ interface, mlpack also provides command-line programs, Python bindings, Julia bindings, Go bindings and R bindings. -
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AutoKeras
AutoML library for deep learning
AutoKeras: An AutoML system based on Keras. It is developed by DATA Lab at Texas A&M University. The goal of AutoKeras is to make machine learning accessible to everyone. AutoKeras only support Python 3. If you followed previous steps to use virtualenv to install tensorflow, you can just activate the virtualenv. Currently, AutoKeras is only compatible with Python >= 3.7 and TensorFlow >= 2.8.0. -
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HumanSystemOptimization
Healthy Learning to 150 - An Incomplete Guide to Human System Tuning
HumanSystemOptimization is a long-form personal guide about health, learning, productivity, and daily habits rather than a software application. It summarizes ideas the author gathered from neuroscience podcasts, research discussions, and personal experimentation. Major sections discuss sleep, circadian rhythms, diet, exercise, focus, mood, learning, and other aspects of everyday performance. The repository mixes background explanations with practical routines and links to outside material... -
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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. ...
