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TensorFlow Learning Guide

A comprehensive Jupyter notebook covering TensorFlow fundamentals and tensor operations.

Overview

This repository contains a detailed exploration of TensorFlow concepts including:

  • Tensor creation and manipulation
  • Multi-dimensional tensors (2D, 3D, 4D)
  • Tensor operations (reshape, slice, stack, etc.)
  • Matrix operations (matrix multiplication, inverse, transpose)
  • Advanced tensor operations (gather, scatter, pad, etc.)
  • Attention mechanisms
  • Linear algebra operations

Contents

  • tensor_flow.ipynb - Main Jupyter notebook with code examples and explanations
  • image.png - Supporting image resources

Installation

Prerequisites

  • Python 3.7+
  • Jupyter Notebook

Setup

  1. Clone the repository:
git clone <repository-url>
cd tensor_flow
  1. Install required packages:
pip install -r requirements.txt
  1. Launch Jupyter Notebook:
jupyter notebook tensor_flow.ipynb

Requirements

  • tensorflow
  • numpy

Usage

Open the notebook and run cells sequentially to understand TensorFlow operations and tensor manipulations.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Contributing

Feel free to submit issues and enhancement requests!

Author

Created as a learning resource for TensorFlow fundamentals.

About

just hands on practice

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