Welcome to Nano-AutoGrad’s Documentation!

Introduction

Nano-AutoGrad is a lightweight Python framework for automatic differentiation and gradient computation. It provides a simple and efficient way to perform gradient-based optimization and machine learning tasks.

This documentation aims to provide an in-depth understanding of the framework’s features, usage, and API reference.

Contents

Installation

The installation section provides instructions on how to install Nano-AutoGrad and its dependencies.

Usage

The usage section guides you through the steps of setting up your project with Nano-AutoGrad and demonstrates various use cases and workflows.

API Reference

The API reference provides detailed documentation for all the classes, functions, and modules available in Nano-AutoGrad. It serves as a comprehensive guide to help you explore and utilize the framework’s capabilities.

Examples

The examples section showcases practical code examples that illustrate how to use Nano-AutoGrad for different tasks, such as linear regression, neural networks, and more.

FAQ (Frequently Asked Questions)

The FAQ section addresses common questions, troubleshooting tips, and best practices for using Nano-AutoGrad effectively.

Indices and Tables

  • Index - Index of all terms and keywords used in the documentation.

  • Module Index - Index of all modules and packages in Nano-AutoGrad.

  • Search Page - Search functionality to find specific information within the documentation.