From 7326026ff93307a436c7196d81c879c45e1e6a55 Mon Sep 17 00:00:00 2001 From: Eli <43382407+eli64s@users.noreply.github.com> Date: Tue, 26 Sep 2023 12:51:20 -0500 Subject: [PATCH] Add preview image of README-AI AI/ML template. --- README.md | 65 ++++++++++++++++++++++++++++++++++---------------- pyproject.toml | 2 +- 2 files changed, 45 insertions(+), 22 deletions(-) diff --git a/README.md b/README.md index 62ef54ed..f8090484 100644 --- a/README.md +++ b/README.md @@ -42,6 +42,7 @@ - [📍 Overview](#-overview) - [🎈 Demos](#-demos) - [🤖 Features](#-features) + - [AI and ML README Template Concept](#ai-and-ml-readme-template-concept) - [👩💻 Usage](#-usage) - [🛠 Installation](#-installation) - [⚙️ Configuration](#️-configuration) @@ -93,7 +94,7 @@ This project is currently under development and has an opinionated configuration
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+ ‣ Developing CLI option letting users select from a variety of README styles +‣ Templates for use-cases such as data, machine learning, web development, and more! + |
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+ + +### AI and ML README Template Concept + +- **[Overview](#overview)**: Summary of the projects' objectives, scope, and expected outcomes. +- **[Project Structure](#project-structure)**: Overview of the organization of the projects and their main components. +- **[Data Preprocessing](#data-collection-and-preprocessing)**: Data sources, collection methods, and types of data +- **[Feature Engineering](#feature-engineering)**: importance of feature engineering and its impact on model performance. +- **[Model Architecture and Development](#model-architecture-and-development)**: Model selection, dev strategies, and implemented algorithms. +- **[Training and Validation](#training-and-validation)**: Info on model training procedures, hyperparameter tuning, and validation strategies. +- **[Testing and Evaluation](#testing-and-evaluation)**: Model testing results, performance analysis, and comparison with benchmarks. +- **[Deployment and Integration](#deployment-and-integration)**: Integration with other systems, APIs, and user interfaces +- **[Usage and Maintenance](#usage-and-maintenance)**: User guide on how to use the deployed models and interfaces. +- **[Results and Discussion](#results-and-discussion)**: Implications, limitations, and future work. +- **[Ethical Considerations](#ethical-considerations)**: Ethical aspects, data privacy, and fairness in model predictions. +- **[Contributing](#contributing)**: Procedures for submitting contributions, reporting issues, and proposing enhancements. +- **[Acknowledgements](#acknowledgements)**: References to resources, libraries, and frameworks used. +- **[License](#license)**: Explanation of usage rights, restrictions, and attribution requirements. + + + |
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