Get started with AI using TensorFlow-Tutorials, with 6.0k+ GitHub stars, ideal for startup founders
6,030 stars1,479 forksJupyter NotebookQuality 8/10Updated 8/20/2023100% free ยท open source
What it does
TensorFlow-Tutorials provides a structured introduction to building and deploying AI models using TensorFlow, making it easier for startup founders to get started with AI development
โขWhen you need to quickly prototype and test AI-driven features for your startup
โขWhen your team lacks extensive AI development experience but wants to explore AI capabilities
โขWhen you want to build and deploy scalable AI models with a widely adopted framework like TensorFlow
Quick start
1Navigate to the cloned repository using `cd TensorFlow-Tutorials`
2Open the Jupyter Notebook environment by running `jupyter notebook`
3Load the tutorial notebooks from the `notebooks` directory, such as `01_tensorflow_basics.ipynb`
4Run the cells in the notebook to execute the code samples and experiments
5Explore and modify the `tensorflow_tutorials` Python package in the `src` directory to dive deeper into the code
Ready-to-paste prompt
Run the command `python src/tensorflow_tutorials/mnist.py` to train a simple MNIST model and see the results
Heads up: Ensure you have Python 3.8 or later installed, as TensorFlow-Tutorials may not be compatible with earlier Python versions, and also be aware that some tutorials may require a GPU for efficient computation
Saves to your device
What's inside โ free to inspect
No purchase needed
Read the entire source before you build โ unlike paid marketplaces that hide it behind a buy button.