{"id":23557442,"url":"https://github.com/chanmeng666/advanced-neural-network-applications","last_synced_at":"2026-05-03T05:39:27.373Z","repository":{"id":266942267,"uuid":"847533136","full_name":"ChanMeng666/advanced-neural-network-applications","owner":"ChanMeng666","description":"Practical implementations of perceptron and linear neuron models for classification and regression, with mathematical analysis and visualizations in Jupyter 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returned=1 errno=0 peeraddr=140.82.121.6:443 state=error: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["classification","data-analysis","data-science","educational","gradient-descent","jupyter-notebook","linear-neuron","machine-learning","matplotlib","neural-network","neural-networks","numpy","perceptron","python","regression"],"created_at":"2024-12-26T14:30:41.743Z","updated_at":"2026-05-03T05:39:27.359Z","avatar_url":"https://github.com/ChanMeng666.png","language":"Jupyter Notebook","funding_links":["https://buymeacoffee.com/chanmeng66u"],"categories":[],"sub_categories":[],"readme":"\u003cdiv align=\"center\"\u003e\u003ca name=\"readme-top\"\u003e\u003c/a\u003e\n\n# 🧠 Advanced Neural Network Applications\u003cbr/\u003e\u003ch3\u003ePerceptron \u0026 Linear Neuron Models from Scratch\u003c/h3\u003e\n\nPractical implementations of perceptron and linear neuron models for classification and regression tasks,\u003cbr/\u003e\nfeaturing step-by-step mathematical analysis and interactive visualizations in Jupyter notebooks.\u003cbr/\u003e\nRun everything in your browser with **Binder** or **Google Colab** — no installation required.\n\n[![][github-stars-shield]][github-stars-link]\n[![][github-forks-shield]][github-forks-link]\n[![][github-issues-shield]][github-issues-link]\n[![][github-license-shield]][github-license-link]\n[![][github-contributors-shield]][github-contributors-link]\n[![][github-releasedate-shield]][github-releasedate-link]\n\n**Tech Stack:**\n\n\u003cimg src=\"https://img.shields.io/badge/python-3670A0?style=for-the-badge\u0026logo=python\u0026logoColor=ffdd54\"/\u003e\n\u003cimg src=\"https://img.shields.io/badge/jupyter-%23F37626.svg?style=for-the-badge\u0026logo=jupyter\u0026logoColor=white\"/\u003e\n\u003cimg src=\"https://img.shields.io/badge/numpy-%23013243.svg?style=for-the-badge\u0026logo=numpy\u0026logoColor=white\"/\u003e\n\u003cimg src=\"https://img.shields.io/badge/pandas-%23150458.svg?style=for-the-badge\u0026logo=pandas\u0026logoColor=white\"/\u003e\n\u003cimg src=\"https://img.shields.io/badge/Matplotlib-%23ffffff.svg?style=for-the-badge\u0026logo=Matplotlib\u0026logoColor=black\"/\u003e\n\u003cimg src=\"https://img.shields.io/badge/scikit--learn-%23F7931E.svg?style=for-the-badge\u0026logo=scikit-learn\u0026logoColor=white\"/\u003e\n\n\u003cp align=\"center\"\u003e\n  \u003ca href=\"https://github.com/ChanMeng666/advanced-neural-network-applications/stargazers\"\u003e\n    \u003cimg src=\"https://img.shields.io/badge/⭐_Star_This_Repo-FFD700?style=for-the-badge\u0026logo=github\u0026logoColor=black\" alt=\"Star this repo\"/\u003e\n  \u003c/a\u003e\n  \u0026nbsp;\n  \u003ca href=\"https://buymeacoffee.com/chanmeng66u\"\u003e\n    \u003cimg src=\"https://img.shields.io/badge/☕_Sponsor_Me-FF813F?style=for-the-badge\u0026logo=buymeacoffee\u0026logoColor=white\" alt=\"Sponsor Me\"/\u003e\n  \u003c/a\u003e\n\u003c/p\u003e\n\n**Share This Project**\n\n[![][share-x-shield]][share-x-link]\n[![][share-telegram-shield]][share-telegram-link]\n[![][share-whatsapp-shield]][share-whatsapp-link]\n[![][share-reddit-shield]][share-reddit-link]\n[![][share-weibo-shield]][share-weibo-link]\n[![][share-mastodon-shield]][share-mastodon-link]\n[![][share-linkedin-shield]][share-linkedin-link]\n\n\u003csup\u003eBuilding intuition for neural networks through hands-on implementations and mathematical analysis.\u003c/sup\u003e\n\n\u003c/div\u003e\n\n\u003e [!IMPORTANT]\n\u003e This project demonstrates foundational neural network architectures through hands-on implementations. It covers **perceptron** models for binary classification and **linear neuron** models for regression, with detailed mathematical derivations, step-by-step weight update calculations, and comprehensive visualizations.\n\n\u003cdetails\u003e\n\u003csummary\u003e\u003ckbd\u003e📑 Table of Contents\u003c/kbd\u003e\u003c/summary\u003e\n\n#### TOC\n\n- [🌟 Introduction](#-introduction)\n- [✨ Key Features](#-key-features)\n  - [`1` Perceptron Classification](#1-perceptron-classification)\n  - [`2` Linear Neuron Regression](#2-linear-neuron-regression)\n  - [`*` Additional Features](#-additional-features)\n- [📊 Visualizations](#-visualizations)\n- [🛠️ Tech Stack](#️-tech-stack)\n- [🚀 Try It Online](#-try-it-online)\n- [📚 Notebooks](#-notebooks)\n- [📁 Datasets](#-datasets)\n- [💻 Getting Started](#-getting-started)\n- [📂 Project Structure](#-project-structure)\n- [🤝 Contributing](#-contributing)\n- [❤️ Sponsor](#️-sponsor)\n- [📄 License](#-license)\n- [🙋‍♀️ Author](#️-author)\n\n####\n\n\u003cbr/\u003e\n\n\u003c/details\u003e\n\n\u003c!-- ═══════════════════════════════════════════════════════════════════════════\n     SECTION: Introduction\n     ═══════════════════════════════════════════════════════════════════════════ --\u003e\n\n## 🌟 Introduction\n\n\u003ctable\u003e\n\u003ctr\u003e\n\u003ctd\u003e\n\n\u003ch4\u003eAbout This Project\u003c/h4\u003e\n\nThis repository provides a comprehensive, hands-on introduction to foundational neural network architectures. Through carefully structured Jupyter notebooks, you'll build perceptron and linear neuron models from scratch, understanding every mathematical step along the way.\n\nWhether you're a student learning machine learning for the first time or an educator looking for teaching materials, these notebooks offer clear explanations, reproducible code, and rich visualizations that bring the theory to life.\n\n\u003ch4\u003eWhat You'll Learn\u003c/h4\u003e\n\n- How perceptrons classify data using step activation functions and iterative weight updates\n- How linear neurons perform regression using gradient descent optimization\n- The mathematics behind convergence, learning rates, and decision boundaries\n- How to visualize model behavior in 2D and 3D\n\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/table\u003e\n\n\u003e [!NOTE]\n\u003e - Python 3.x required\n\u003e - No GPU needed — all models run on CPU\n\u003e - Zero-install option available via Binder and Google Colab\n\n\u003e [!TIP]\n\u003e **⭐ Star us** to receive all release notifications from GitHub without delay!\n\n\u003cdetails\u003e\n  \u003csummary\u003e\u003ckbd\u003e⭐ Star History\u003c/kbd\u003e\u003c/summary\u003e\n  \u003cpicture\u003e\n    \u003csource media=\"(prefers-color-scheme: dark)\" srcset=\"https://api.star-history.com/svg?repos=ChanMeng666%2Fadvanced-neural-network-applications\u0026theme=dark\u0026type=Date\"\u003e\n    \u003cimg width=\"100%\" src=\"https://api.star-history.com/svg?repos=ChanMeng666%2Fadvanced-neural-network-applications\u0026type=Date\"\u003e\n  \u003c/picture\u003e\n\u003c/details\u003e\n\n\u003cdiv align=\"right\"\u003e\n\n[![][back-to-top]](#readme-top)\n\n\u003c/div\u003e\n\n\u003c!-- ═══════════════════════════════════════════════════════════════════════════\n     SECTION: Key Features\n     ═══════════════════════════════════════════════════════════════════════════ --\u003e\n\n## ✨ Key Features\n\n### `1` Perceptron Classification\n\nBinary classification of fish species (Canadian vs. Alaskan) using step activation functions and iterative weight updates. Includes convergence proofs and classification boundary visualization.\n\n\u003cdiv align=\"center\"\u003e\n  \u003cimg src=\"images/perceptron-classification-boundaries.png\" alt=\"Perceptron Classification Boundaries\" width=\"600\"/\u003e\n  \u003cp\u003e\u003cem\u003ePerceptron classification boundaries for fish species identification\u003c/em\u003e\u003c/p\u003e\n\u003c/div\u003e\n\nKey capabilities include:\n- 🐟 **Fish Species Classification**: Distinguish Canadian from Alaskan fish using ring diameter measurements\n- 📐 **Mathematical Derivations**: Step-by-step weight update calculations with full working\n- 📈 **Convergence Analysis**: Proof of convergence and boundary evolution visualization\n- 🎯 **Decision Boundaries**: Interactive plotting of classification boundaries\n\n[![][back-to-top]](#readme-top)\n\n### `2` Linear Neuron Regression\n\nRegression for predicting building heat influx from elevation measurements, using gradient descent optimization. Progresses from single-input to multi-input models with 3D visualization.\n\n\u003cdiv align=\"center\"\u003e\n  \u003cimg src=\"images/3d-predicted-heat-influx.png\" alt=\"3D Predicted Heat Influx\" width=\"600\"/\u003e\n  \u003cp\u003e\u003cem\u003e3D surface plot of predicted heat influx with actual data points\u003c/em\u003e\u003c/p\u003e\n\u003c/div\u003e\n\nKey capabilities include:\n- 🏗️ **Heat Influx Prediction**: Predict building heat influx from north and south elevation data\n- 📉 **Gradient Descent**: Learning rate tuning and convergence analysis\n- 🔄 **Single \u0026 Multi-Input**: Progressive complexity from 1D to 2D feature spaces\n- 🌐 **3D Visualization**: Interactive prediction surface rendering\n\n[![][back-to-top]](#readme-top)\n\n### `*` Additional Features\n\nBeyond the core models, this project includes:\n\n- [x] 📝 **Detailed Math**: Complete mathematical derivations for every weight update step\n- [x] 🎓 **Structured Learning Path**: 7 notebooks in recommended sequential order\n- [x] ☁️ **Zero Installation**: Run everything in Binder or Google Colab\n- [x] 📊 **Rich Visualizations**: 2D plots, 3D surfaces, and comparison charts\n- [x] ✅ **Model Validation**: Testing procedures and accuracy evaluation\n- [x] 🔧 **Optimization Analysis**: Learning rate tuning and convergence studies\n- [x] 📂 **Clean Datasets**: Well-documented CSV files ready for exploration\n\n\u003e ✨ An ideal resource for learning the foundations of neural networks.\n\n\u003cdiv align=\"right\"\u003e\n\n[![][back-to-top]](#readme-top)\n\n\u003c/div\u003e\n\n\u003c!-- ═══════════════════════════════════════════════════════════════════════════\n     SECTION: Visualizations\n     ═══════════════════════════════════════════════════════════════════════════ --\u003e\n\n## 📊 Visualizations\n\n\u003cdiv align=\"center\"\u003e\n  \u003ctable\u003e\n    \u003ctr\u003e\n      \u003ctd width=\"50%\" align=\"center\"\u003e\n        \u003cimg src=\"images/perceptron-classification-boundaries.png\" alt=\"Perceptron Classification Boundaries\" width=\"100%\"/\u003e\n        \u003cbr/\u003e\u003cem\u003ePerceptron Classification Boundaries\u003c/em\u003e\n      \u003c/td\u003e\n      \u003ctd width=\"50%\" align=\"center\"\u003e\n        \u003cimg src=\"images/3d-predicted-heat-influx.png\" alt=\"3D Predicted Heat Influx\" width=\"100%\"/\u003e\n        \u003cbr/\u003e\u003cem\u003e3D Predicted Heat Influx Surface\u003c/em\u003e\n      \u003c/td\u003e\n    \u003c/tr\u003e\n  \u003c/table\u003e\n\u003c/div\u003e\n\n\u003cdetails\u003e\n\u003csummary\u003e\u003ckbd\u003e📈 More Visualizations\u003c/kbd\u003e\u003c/summary\u003e\n\n\u003cdiv align=\"center\"\u003e\n  \u003ctable\u003e\n    \u003ctr\u003e\n      \u003ctd width=\"50%\" align=\"center\"\u003e\n        \u003cimg src=\"images/actual-vs-predicted-heat-influx-1.png\" alt=\"Actual vs Predicted Heat Influx\" width=\"100%\"/\u003e\n        \u003cbr/\u003e\u003cem\u003eActual vs Predicted Heat Influx\u003c/em\u003e\n      \u003c/td\u003e\n      \u003ctd width=\"50%\" align=\"center\"\u003e\n        \u003cimg src=\"images/actual-vs-predicted-heat-influx-2.png\" alt=\"Actual vs Predicted Heat Influx 2\" width=\"100%\"/\u003e\n        \u003cbr/\u003e\u003cem\u003eDetailed Comparison Analysis\u003c/em\u003e\n      \u003c/td\u003e\n    \u003c/tr\u003e\n    \u003ctr\u003e\n      \u003ctd width=\"50%\" align=\"center\"\u003e\n        \u003cimg src=\"images/optimized-linear-model-fit-1.png\" alt=\"Optimized Linear Model Fit\" width=\"100%\"/\u003e\n        \u003cbr/\u003e\u003cem\u003eOptimized Linear Model Fit\u003c/em\u003e\n      \u003c/td\u003e\n      \u003ctd width=\"50%\" align=\"center\"\u003e\n        \u003cimg src=\"images/optimized-linear-model-fit-2.png\" alt=\"Optimized Linear Model Fit 2\" width=\"100%\"/\u003e\n        \u003cbr/\u003e\u003cem\u003eEnhanced Optimization Results\u003c/em\u003e\n      \u003c/td\u003e\n    \u003c/tr\u003e\n  \u003c/table\u003e\n\u003c/div\u003e\n\n\u003c/details\u003e\n\n\u003cdiv align=\"right\"\u003e\n\n[![][back-to-top]](#readme-top)\n\n\u003c/div\u003e\n\n\u003c!-- ═══════════════════════════════════════════════════════════════════════════\n     SECTION: Tech Stack\n     ═══════════════════════════════════════════════════════════════════════════ --\u003e\n\n## 🛠️ Tech Stack\n\n\u003cdiv align=\"center\"\u003e\n  \u003ctable\u003e\n    \u003ctr\u003e\n      \u003ctd align=\"center\" width=\"96\"\u003e\n        \u003cimg src=\"https://cdn.simpleicons.org/python\" width=\"48\" height=\"48\" alt=\"Python\" /\u003e\n        \u003cbr\u003ePython 3.x\n      \u003c/td\u003e\n      \u003ctd align=\"center\" width=\"96\"\u003e\n        \u003cimg src=\"https://cdn.simpleicons.org/jupyter\" width=\"48\" height=\"48\" alt=\"Jupyter\" /\u003e\n        \u003cbr\u003eJupyter\n      \u003c/td\u003e\n      \u003ctd align=\"center\" width=\"96\"\u003e\n        \u003cimg src=\"https://cdn.simpleicons.org/numpy\" width=\"48\" height=\"48\" alt=\"NumPy\" /\u003e\n        \u003cbr\u003eNumPy\n      \u003c/td\u003e\n      \u003ctd align=\"center\" width=\"96\"\u003e\n        \u003cimg src=\"https://cdn.simpleicons.org/pandas\" width=\"48\" height=\"48\" alt=\"Pandas\" /\u003e\n        \u003cbr\u003ePandas\n      \u003c/td\u003e\n      \u003ctd align=\"center\" width=\"96\"\u003e\n        \u003ca href=\"https://matplotlib.org\"\u003e\u003cimg src=\"https://upload.wikimedia.org/wikipedia/commons/8/84/Matplotlib_icon.svg\" width=\"48\" height=\"48\" alt=\"Matplotlib\" /\u003e\u003c/a\u003e\n        \u003cbr\u003eMatplotlib\n      \u003c/td\u003e\n      \u003ctd align=\"center\" width=\"96\"\u003e\n        \u003cimg src=\"https://cdn.simpleicons.org/scikitlearn\" width=\"48\" height=\"48\" alt=\"Scikit-learn\" /\u003e\n        \u003cbr\u003eScikit-learn\n      \u003c/td\u003e\n    \u003c/tr\u003e\n  \u003c/table\u003e\n\u003c/div\u003e\n\n- **Python** — implementation language\n- **Jupyter Notebook** — interactive development environment\n- **NumPy** — numerical computing and matrix operations\n- **Pandas** — data loading and manipulation\n- **Matplotlib** — plotting and visualization\n- **Scikit-learn** — evaluation metrics and utilities\n\n\u003cdiv align=\"right\"\u003e\n\n[![][back-to-top]](#readme-top)\n\n\u003c/div\u003e\n\n\u003c!-- ═══════════════════════════════════════════════════════════════════════════\n     SECTION: Try It Online\n     ═══════════════════════════════════════════════════════════════════════════ --\u003e\n\n## 🚀 Try It Online\n\nYou can run all notebooks directly in your browser — no local installation required:\n\n\u003cdiv align=\"center\"\u003e\n\n[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/ChanMeng666/advanced-neural-network-applications/main?labpath=notebooks)\n\u0026nbsp;\u0026nbsp;\n[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/ChanMeng666/advanced-neural-network-applications/blob/main/notebooks/01-perceptron-basics.ipynb)\n\n\u003c/div\u003e\n\n- **Binder** — launch the full interactive environment with all notebooks\n- **Google Colab** — open individual notebooks via the links in the [Notebooks](#-notebooks) table below\n\n\u003cdiv align=\"center\"\u003e\n  \u003cimg src=\"images/mybinder.org.png\" alt=\"Binder screenshot — running notebooks in the browser\" width=\"800\"/\u003e\n  \u003cp\u003e\u003cem\u003eRunning notebooks interactively on Binder\u003c/em\u003e\u003c/p\u003e\n\u003c/div\u003e\n\n\u003cdiv align=\"right\"\u003e\n\n[![][back-to-top]](#readme-top)\n\n\u003c/div\u003e\n\n\u003c!-- ═══════════════════════════════════════════════════════════════════════════\n     SECTION: Notebooks\n     ═══════════════════════════════════════════════════════════════════════════ --\u003e\n\n## 📚 Notebooks\n\n| # | Notebook | Topic | Description | Colab |\n|---|----------|-------|-------------|-------|\n| 1 | [01-perceptron-basics](notebooks/01-perceptron-basics.ipynb) | Perceptron | Binary classification with fish species data, weight initialization, activation functions | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/ChanMeng666/advanced-neural-network-applications/blob/main/notebooks/01-perceptron-basics.ipynb) |\n| 2 | [02-perceptron-analysis](notebooks/02-perceptron-analysis.ipynb) | Perceptron | Mathematical analysis, convergence proofs, classification boundary visualization | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/ChanMeng666/advanced-neural-network-applications/blob/main/notebooks/02-perceptron-analysis.ipynb) |\n| 3 | [03-linear-neuron-single-input](notebooks/03-linear-neuron-single-input.ipynb) | Linear Neuron | Single-input regression predicting heat influx from north elevation | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/ChanMeng666/advanced-neural-network-applications/blob/main/notebooks/03-linear-neuron-single-input.ipynb) |\n| 4 | [04-linear-neuron-optimization](notebooks/04-linear-neuron-optimization.ipynb) | Optimization | Learning rate tuning, gradient descent, convergence analysis | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/ChanMeng666/advanced-neural-network-applications/blob/main/notebooks/04-linear-neuron-optimization.ipynb) |\n| 5 | [05-linear-neuron-multi-input](notebooks/05-linear-neuron-multi-input.ipynb) | Linear Neuron | Multi-input regression using north and south elevation measurements | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/ChanMeng666/advanced-neural-network-applications/blob/main/notebooks/05-linear-neuron-multi-input.ipynb) |\n| 6 | [06-linear-neuron-validation](notebooks/06-linear-neuron-validation.ipynb) | Validation | Model validation and testing procedures | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/ChanMeng666/advanced-neural-network-applications/blob/main/notebooks/06-linear-neuron-validation.ipynb) |\n| 7 | [07-linear-neuron-3d-visualization](notebooks/07-linear-neuron-3d-visualization.ipynb) | Visualization | Interactive 3D prediction surface rendering | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/ChanMeng666/advanced-neural-network-applications/blob/main/notebooks/07-linear-neuron-3d-visualization.ipynb) |\n\n**Recommended learning path:** Start with notebook 01, then progress sequentially through the series.\n\n\u003cdiv align=\"right\"\u003e\n\n[![][back-to-top]](#readme-top)\n\n\u003c/div\u003e\n\n\u003c!-- ═══════════════════════════════════════════════════════════════════════════\n     SECTION: Datasets\n     ═══════════════════════════════════════════════════════════════════════════ --\u003e\n\n## 📁 Datasets\n\n### Fish Classification (`data/fish_data.csv`)\n\nBinary classification dataset with 94 fish measurements:\n- **Features:** freshwater ring diameter, saltwater ring diameter\n- **Target:** species label (0 = Canadian, 1 = Alaskan)\n\n### Heat Influx (`data/heat_influx_north_south.csv`)\n\nRegression dataset with 29 building observations:\n- **Features:** north and south elevation measurements\n- **Target:** heat influx (continuous)\n\n\u003cdiv align=\"right\"\u003e\n\n[![][back-to-top]](#readme-top)\n\n\u003c/div\u003e\n\n\u003c!-- ═══════════════════════════════════════════════════════════════════════════\n     SECTION: Getting Started\n     ═══════════════════════════════════════════════════════════════════════════ --\u003e\n\n## 💻 Getting Started\n\n\u003e [!TIP]\n\u003e Prefer not to install anything? Use [Binder](https://mybinder.org/v2/gh/ChanMeng666/advanced-neural-network-applications/main?labpath=notebooks) or [Google Colab](#-notebooks) to run notebooks directly in your browser.\n\n### Prerequisites\n\n- Python 3.x ([Download](https://python.org))\n- pip (Python package manager)\n- Git ([Download](https://git-scm.com))\n\n### Installation\n\n```bash\ngit clone https://github.com/ChanMeng666/advanced-neural-network-applications.git\ncd advanced-neural-network-applications\npip install -r requirements.txt\n```\n\n### Running the Notebooks\n\n```bash\njupyter notebook\n# or\njupyter lab\n```\n\nThen open any notebook from the `notebooks/` directory. Notebooks load data using relative paths, so they work out of the box when launched from the project root.\n\n\u003cdiv align=\"right\"\u003e\n\n[![][back-to-top]](#readme-top)\n\n\u003c/div\u003e\n\n\u003c!-- ═══════════════════════════════════════════════════════════════════════════\n     SECTION: Project Structure\n     ═══════════════════════════════════════════════════════════════════════════ --\u003e\n\n## 📂 Project Structure\n\n```\nadvanced-neural-network-applications/\n├── .github/\n│   ├── FUNDING.yml\n│   ├── ISSUE_TEMPLATE/\n│   │   ├── bug_report.md\n│   │   └── feature_request.md\n│   └── workflows/\n│       └── update-license-year.yml\n├── data/\n│   ├── fish_data.csv\n│   └── heat_influx_north_south.csv\n├── images/\n│   └── (visualization outputs)\n├── notebooks/\n│   ├── 01-perceptron-basics.ipynb\n│   ├── 02-perceptron-analysis.ipynb\n│   ├── 03-linear-neuron-single-input.ipynb\n│   ├── 04-linear-neuron-optimization.ipynb\n│   ├── 05-linear-neuron-multi-input.ipynb\n│   ├── 06-linear-neuron-validation.ipynb\n│   └── 07-linear-neuron-3d-visualization.ipynb\n├── CHANGELOG.md\n├── CITATION.cff\n├── CODE_OF_CONDUCT.md\n├── CONTRIBUTING.md\n├── LICENSE\n├── PULL_REQUEST_TEMPLATE.md\n├── README.md\n├── SECURITY.md\n├── SUPPORT.md\n└── requirements.txt\n```\n\n\u003cdiv align=\"right\"\u003e\n\n[![][back-to-top]](#readme-top)\n\n\u003c/div\u003e\n\n\u003c!-- ═══════════════════════════════════════════════════════════════════════════\n     SECTION: Contributing\n     ═══════════════════════════════════════════════════════════════════════════ --\u003e\n\n## 🤝 Contributing\n\nContributions are welcome! Here's how you can help improve this project:\n\n1. Fork the repository\n2. Create a feature branch (`git checkout -b feature/your-feature`)\n3. Commit your changes\n4. Push to the branch and open a pull request\n\nPlease read our [Contributing Guidelines](CONTRIBUTING.md) for detailed instructions and follow our [Code of Conduct](CODE_OF_CONDUCT.md). For security concerns, see [SECURITY.md](SECURITY.md). For help, see [SUPPORT.md](SUPPORT.md).\n\n[![][pr-welcome-shield]][pr-welcome-link]\n\n### Contributors\n\n\u003ca href=\"https://github.com/ChanMeng666/advanced-neural-network-applications/graphs/contributors\"\u003e\n  \u003cimg src=\"https://contrib.rocks/image?repo=ChanMeng666/advanced-neural-network-applications\" /\u003e\n\u003c/a\u003e\n\n\u003cdiv align=\"right\"\u003e\n\n[![][back-to-top]](#readme-top)\n\n\u003c/div\u003e\n\n\u003c!-- ═══════════════════════════════════════════════════════════════════════════\n     SECTION: Sponsor\n     ═══════════════════════════════════════════════════════════════════════════ --\u003e\n\n## ❤️ Sponsor\n\nIf this project helped you learn, consider supporting its development!\n\n\u003cp align=\"center\"\u003e\n  \u003ca href=\"https://github.com/ChanMeng666/advanced-neural-network-applications/stargazers\"\u003e\n    \u003cimg src=\"https://img.shields.io/badge/⭐_Star_it_on_GitHub-FFD700?style=for-the-badge\u0026logo=github\u0026logoColor=black\" alt=\"Star on GitHub\"/\u003e\n  \u003c/a\u003e\n  \u0026nbsp;\u0026nbsp;\n  \u003ca href=\"https://buymeacoffee.com/chanmeng66u\"\u003e\n    \u003cimg src=\"https://img.shields.io/badge/☕_Buy_Me_A_Coffee-FF813F?style=for-the-badge\u0026logo=buymeacoffee\u0026logoColor=white\" alt=\"Buy Me A Coffee\"/\u003e\n  \u003c/a\u003e\n\u003c/p\u003e\n\n\u003cp align=\"center\"\u003e\n  \u003ca href=\"https://buymeacoffee.com/chanmeng66u\" target=\"_blank\"\u003e\n    \u003cimg src=\"https://cdn.buymeacoffee.com/buttons/v2/default-yellow.png\" alt=\"Buy Me A Coffee\" height=\"50\"\u003e\n  \u003c/a\u003e\n\u003c/p\u003e\n\n### Thanks to all the kind people! 💖\n\n**Stargazers**\n\n\u003cp align=\"center\"\u003e\n  \u003ca href=\"https://github.com/ChanMeng666/advanced-neural-network-applications/stargazers\"\u003e\n    \u003cimg src=\"https://bytecrank.com/nastyox/reporoster/php/stargazersSVG.php?user=ChanMeng666\u0026repo=advanced-neural-network-applications\" alt=\"Stargazers repo roster for @ChanMeng666/advanced-neural-network-applications\"/\u003e\n  \u003c/a\u003e\n\u003c/p\u003e\n\n**Forkers**\n\n\u003cp align=\"center\"\u003e\n  \u003ca href=\"https://github.com/ChanMeng666/advanced-neural-network-applications/network/members\"\u003e\n    \u003cimg src=\"https://bytecrank.com/nastyox/reporoster/php/forkersSVG.php?user=ChanMeng666\u0026repo=advanced-neural-network-applications\" alt=\"Forkers repo roster for @ChanMeng666/advanced-neural-network-applications\"/\u003e\n  \u003c/a\u003e\n\u003c/p\u003e\n\n\u003cdiv align=\"right\"\u003e\n\n[![][back-to-top]](#readme-top)\n\n\u003c/div\u003e\n\n\u003c!-- ═══════════════════════════════════════════════════════════════════════════\n     SECTION: License\n     ═══════════════════════════════════════════════════════════════════════════ --\u003e\n\n## 📄 License\n\nThis project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.\n\n\u003c!-- ═══════════════════════════════════════════════════════════════════════════\n     SECTION: Author\n     ═══════════════════════════════════════════════════════════════════════════ --\u003e\n\n## 🙋‍♀️ Author\n\n**Chan Meng**\n\n\u003cp\u003e\n  \u003ca href=\"https://www.linkedin.com/in/chanmeng666/\"\u003e\n    \u003cimg src=\"https://img.shields.io/badge/LinkedIn-chanmeng666-0A66C2?style=flat\u0026logo=linkedin\u0026logoColor=white\" alt=\"LinkedIn\"/\u003e\n  \u003c/a\u003e\n  \u003ca href=\"https://github.com/ChanMeng666\"\u003e\n    \u003cimg src=\"https://img.shields.io/badge/GitHub-ChanMeng666-181717?style=flat\u0026logo=github\u0026logoColor=white\" alt=\"GitHub\"/\u003e\n  \u003c/a\u003e\n  \u003ca href=\"mailto:chanmeng.dev@gmail.com\"\u003e\n    \u003cimg src=\"https://img.shields.io/badge/Email-chanmeng.dev@gmail.com-EA4335?style=flat\u0026logo=gmail\u0026logoColor=white\" alt=\"Email\"/\u003e\n  \u003c/a\u003e\n  \u003ca href=\"https://chanmeng.org/\"\u003e\n    \u003cimg src=\"https://img.shields.io/badge/Website-chanmeng.org-4285F4?style=flat\u0026logo=googlechrome\u0026logoColor=white\" alt=\"Website\"/\u003e\n  \u003c/a\u003e\n\u003c/p\u003e\n\n---\n\n\u003cdiv align=\"center\"\u003e\n\u003cstrong\u003e🧠 Building Intuition for Neural Networks 🌟\u003c/strong\u003e\n\u003cbr/\u003e\n\u003cem\u003eLearn the fundamentals through hands-on implementations\u003c/em\u003e\n\u003cbr/\u003e\u003cbr/\u003e\n\n⭐ **Star us on GitHub** · 📖 **Read the Notebooks** · 🐛 **Report Issues** · 💡 **Request Features** · 🤝 **Contribute**\n\n\u003cbr/\u003e\n\n\u003cimg src=\"https://img.shields.io/github/stars/ChanMeng666/advanced-neural-network-applications?style=social\" alt=\"GitHub stars\"\u003e\n\u003cimg 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