### Top-Level Files Example Source: https://github.com/josephmisiti/awesome-machine-learning/blob/master/_autodocs/patterns-and-conventions.md Shows the structure of top-level files and directories in the project repository. ```markdown README.md — Main curated list LICENSE — MIT license scripts/ pull_R_packages.py — Maintenance utility requirements.txt — Python dependencies ``` -------------------------------- ### Generated Package List Example Source: https://github.com/josephmisiti/awesome-machine-learning/blob/master/_autodocs/api-reference/pull_R_packages.md Shows a sample of the markdown-formatted output that will be created in the Packages.txt file. ```markdown * [Package1](http://cran.r-project.org/web/packages/package1) - Description of package 1 * [Package2](http://cran.r-project.org/web/packages/package2) - Description of package 2 ``` -------------------------------- ### Install Python Dependencies Source: https://github.com/josephmisiti/awesome-machine-learning/blob/master/_autodocs/configuration.md Installs all required Python packages listed in 'scripts/requirements.txt'. Alternatively, packages can be installed individually. ```bash pip install -r scripts/requirements.txt ``` ```bash pip install pyquery urllib3 ``` -------------------------------- ### Go Domain Coverage Example Source: https://github.com/josephmisiti/awesome-machine-learning/blob/master/_autodocs/content-structure.md Summarizes the domain coverage for Go within the repository, highlighting its strongest areas. ```text 6 categories - Strongest in: General-purpose ML, NLP, Data Visualization ``` -------------------------------- ### Example Output Format Source: https://github.com/josephmisiti/awesome-machine-learning/blob/master/_autodocs/api-reference/pull_R_packages.md Illustrates the markdown format used for listing R packages and their descriptions in the output file. ```markdown * [PackageName](http://cran.r-project.org/web/...) - Package Description ``` -------------------------------- ### C++ Domain Coverage Example Source: https://github.com/josephmisiti/awesome-machine-learning/blob/master/_autodocs/content-structure.md Summarizes the domain coverage for C++ within the repository, highlighting its strongest areas. ```text 7 categories - Strongest in: Computer Vision, General-purpose ML, Speech Recognition ``` -------------------------------- ### Library Naming Convention Example Source: https://github.com/josephmisiti/awesome-machine-learning/blob/master/_autodocs/patterns-and-conventions.md Illustrates how to handle special characters in library names by avoiding URLs and using descriptions. ```markdown * [cONNXr](https://github.com/alrevuelta/cONNXr) - An ONNX runtime written in pure C (99) ``` -------------------------------- ### Markdown List Example Source: https://github.com/josephmisiti/awesome-machine-learning/blob/master/_autodocs/patterns-and-conventions.md Illustrates consistent ordering within a category using a markdown list. ```markdown #### General-Purpose Machine Learning * [Library A](...) * [Library B](...) * [Library C](...) ``` -------------------------------- ### Category-Specific Files Example Source: https://github.com/josephmisiti/awesome-machine-learning/blob/master/_autodocs/patterns-and-conventions.md Lists common category-specific markdown files used for organizing ML resources. ```markdown books.md — Free ML books courses.md — Online education blogs.md — Blogs and newsletters events.md — Conferences and events meetups.md — Local communities ml-curriculum.md — Structured learning paths ``` -------------------------------- ### Python Domain Coverage Example Source: https://github.com/josephmisiti/awesome-machine-learning/blob/master/_autodocs/content-structure.md Summarizes the domain coverage for Python within the repository, highlighting its strongest areas. ```text 8 categories + Misc = Comprehensive coverage - Strongest in: Deep Learning, NLP, Computer Vision, Data Analysis ``` -------------------------------- ### Section Hierarchy: Level 1 and Level 2 Examples Source: https://github.com/josephmisiti/awesome-machine-learning/blob/master/_autodocs/patterns-and-conventions.md Illustrates the markdown for language and category headings. ```markdown ## Python ## C++ ## Java ## JavaScript ``` ```markdown #### General-Purpose Machine Learning #### Computer Vision #### Natural Language Processing ``` -------------------------------- ### Python Section Structure Example Source: https://github.com/josephmisiti/awesome-machine-learning/blob/master/_autodocs/content-structure.md Illustrates the hierarchical organization of Python libraries within the repository, categorized by machine learning domains. ```bash ## Python ├── Computer Vision │ ├── Library 1 │ ├── Library 2 │ └── ... ├── Natural Language Processing │ ├── Library 1 │ ├── Library 2 │ └── ... ├── General-Purpose Machine Learning │ ├── Library 1 │ ├── Library 2 │ └── ... ├── Data Analysis / Data Visualization │ ├── Library 1 │ ├── Library 2 │ └── ... ├── Neural Networks │ ├── Library 1 │ ├── Library 2 │ └── ... ├── Survival Analysis │ ├── Library 1 │ └── ... ├── Federated Learning │ ├── Library 1 │ └── ... ├── Kaggle Competition Source Code │ ├── Library 1 │ └── ... ├── Reinforcement Learning │ ├── Library 1 │ ├── Library 2 │ └── ... ├── Speech Recognition │ ├── Library 1 │ └── ... └── Misc Scripts / iPython Notebooks ├── Library 1 └── ... ``` -------------------------------- ### Markdown Spacing and Anchor Example Source: https://github.com/josephmisiti/awesome-machine-learning/blob/master/_autodocs/patterns-and-conventions.md Demonstrates markdown formatting with anchor tags for navigation and spacing between language and category sections. ```markdown ## Python #### Computer Vision * [OpenCV](...) * [DLib](...) #### Natural Language Processing * [NLTK](...) * [spaCy](...) ``` -------------------------------- ### URL Standard: Canonical Reference Example Source: https://github.com/josephmisiti/awesome-machine-learning/blob/master/_autodocs/patterns-and-conventions.md Demonstrates linking to the primary or official fork URL for a library, even if it has moved or forked. ```markdown * [Vowpal Wabbit (VW)](https://github.com/VowpalWabbit/vowpal_wabbit) - A fast out-of-core learning system. ``` -------------------------------- ### Understand the Project Source: https://github.com/josephmisiti/awesome-machine-learning/blob/master/_autodocs/QUICKSTART.md Read the main README.md to understand the nature of the project. This is a curated list, not a library. ```text Read: README.md Learn: This is a curated list, not a library ``` -------------------------------- ### Status Marker: Deprecation Tag Example Source: https://github.com/josephmisiti/awesome-machine-learning/blob/master/_autodocs/patterns-and-conventions.md An example of a deprecated library entry. ```markdown * [naive-apl](https://github.com/mattcunningham/naive-apl) - Naive Bayesian Classifier implementation in APL. **[Deprecated]** ``` -------------------------------- ### Description Pattern: Data Tools Source: https://github.com/josephmisiti/awesome-machine-learning/blob/master/_autodocs/patterns-and-conventions.md Example of a description for a data analysis tool. ```markdown * [Pandas](https://...) - Data structures and data analysis tools for Python. ``` -------------------------------- ### Description Pattern: Language/DSL Source: https://github.com/josephmisiti/awesome-machine-learning/blob/master/_autodocs/patterns-and-conventions.md Example of a description for a programming language or domain-specific language. ```markdown * [Julia](https://...) - High-level dynamic programming language for numerical computing. ``` -------------------------------- ### Contribute to the Project Source: https://github.com/josephmisiti/awesome-machine-learning/blob/master/_autodocs/QUICKSTART.md Read patterns-and-conventions.md to learn how to add new libraries. Follow the contribution guidelines in repository-overview.md. ```text Read: patterns-and-conventions.md Learn: How to add new libraries Follow: Contribution guidelines in repository-overview.md ``` -------------------------------- ### Find ML Frameworks Source: https://github.com/josephmisiti/awesome-machine-learning/blob/master/_autodocs/QUICKSTART.md Read content-structure.md to learn how the repository is organized. Then, open the main README.md in the repository to browse frameworks. ```text Read: content-structure.md Learn: How the repository is organized Open: Main README.md in the repository ``` -------------------------------- ### Description Pattern: Deep Learning Frameworks Source: https://github.com/josephmisiti/awesome-machine-learning/blob/master/_autodocs/patterns-and-conventions.md Example of a description for a deep learning framework. ```markdown * [TensorFlow](https://...) - Open source software library for machine learning with flexible ecosystem of tools. ``` -------------------------------- ### Command Line Usage Source: https://github.com/josephmisiti/awesome-machine-learning/blob/master/_autodocs/api-reference/pull_R_packages.md Execute the script from the command line to generate the Packages.txt file. ```bash python scripts/pull_R_packages.py ``` -------------------------------- ### Description Pattern: Algorithm/Method Libraries Source: https://github.com/josephmisiti/awesome-machine-learning/blob/master/_autodocs/patterns-and-conventions.md Example of a description for a library focused on algorithms and methods. ```markdown * [scikit-learn](https://...) - Machine learning library for Python featuring supervised and unsupervised learning algorithms. ```