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Back to internlm/tutorial

Open-source alternatives to Tutorial

30 open-source projects similar to internlm/tutorial, ranked by how many features they have in common. Compare stars, activity and what each one does to find the best Tutorial alternative.

  • adambard/learnxinyminutes-docsadambard 的头像

    adambard/learnxinyminutes-docs

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    This project is a collection of programming language references and syntax cheat sheets designed for rapid developer onboarding. It serves as a library of code-based documentation that uses valid source code files to provide whirlwind tours of various language specifications. The project focuses on programming language learning by providing concise, commented code examples that explain core features and syntax in place. This approach enables developers to quickly grasp language-specific patterns, data types, and execution flow through a consistent reference format. The content covers a broad

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  • adrianmoisey/learn-pythonadrianmoisey 的头像

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    240在 GitHub 上查看↗

    A collection of links that teach python

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    This is a machine learning educational repository consisting of a collection of notebooks and code examples. It provides practical implementations of diverse machine learning algorithms and workflows, ranging from traditional scientific computing to deep learning. The project features specific implementations of Scikit-Learn models, such as decision trees, random forests, and support vector machines, as well as TensorFlow examples for building neural networks, convolutional layers, and recurrent architectures. It also includes tutorials on reinforcement learning development and the creation o

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  • alex/what-happens-whenalex 的头像

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    43,189在 GitHub 上查看↗

    This project is a collaborative knowledge base and technical learning resource that provides a detailed breakdown of the internal processes occurring within modern computing environments. It serves as a comprehensive educational reference, tracing the step-by-step operations triggered by common user interactions and network requests to explain how hardware and software components interact across the entire stack. The guide distinguishes itself by offering deep technical insights into the journey from physical input to visual output. It covers the low-level mechanics of hardware interrupt hand

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    This is an Asciidoc book of Simon Wardley's "Wardley Maps". It simply takes all his medium posts and joins them together for ease of reading. The intention is to be entirely faithful to the original posts - I've not even fixed the few spelling mistakes - while allowing various output versions to…

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    Fuzzing101 is an educational resource providing a structured curriculum and containerized security labs for learning software fuzzing and vulnerability research. It functions as a training course that guides users through the process of identifying security flaws using systematic input manipulation and memory corruption analysis. The project distinguishes itself by providing isolated environments that ensure consistent build dependencies for practicing software instrumentation and crash triaging. It includes a practical tutorial on using evolutionary fuzzing engines and instrumentation tools

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    This project provides educational materials and courseware focused on the theoretical and practical foundations of distributed systems design. It serves as a comprehensive curriculum covering the disciplines of consensus, data consistency, reliability engineering, and scalability. The instructional content focuses on achieving cluster agreement through consensus algorithms and managing system-wide state via coordination frameworks. It includes a dedicated guide to data theory, exploring replication strategies, consistency models, and data convergence. The courseware covers a broad capability

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    Curated list: Resources for machine learning in Ruby

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    151在 GitHub 上查看↗

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    Podcast about Android Development with Hannes Dorfmann, Artem Zinnatullin, Artur Dryomov and wonderful guests!

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    This project is a collection of structured study notes and notebooks serving as an educational resource for deep learning and neural network fundamentals. It provides a technical reference for implementing machine learning theory, covering everything from basic network design to the construction of advanced architectures. The material specifically focuses on the implementation of convolutional neural networks for computer vision and sequence models for natural language processing. It includes detailed guidance on building object detection systems, face recognition, and speech transcription mo

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    A curated list of applied machine learning and data science notebooks and libraries across different industries.

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    awesomedata/awesome-public-datasets

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    This project is a community-maintained, open-access directory of high-quality public datasets. It serves as a centralized reference point for researchers, developers, and data scientists to locate reliable information sources across a wide spectrum of industries and scientific fields. By providing a structured index, the repository facilitates the discovery of data necessary for exploratory analysis, machine learning model training, and the development of data-intensive applications. The directory distinguishes itself through a lightweight, platform-agnostic approach to resource indexing that

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    ` ENDPOINT /search?q={query} GET https://kbbi-api-amm.herokuapp.com/search?q=apel `

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    Must-watch videos about javascript

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    HelloGitHub is a centralized discovery platform and technical knowledge repository designed to help developers identify high-quality open-source projects, libraries, and infrastructure. It functions as a structured directory that aggregates specialized development tools and educational materials, organizing them by technical domain to facilitate efficient resource discovery and professional development. The platform distinguishes itself through a community-driven curation workflow, where manual editorial oversight filters the broader software ecosystem into thematic collections. This content

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