Terry Um’s TensorFlow Exercises
A collection of TensorFlow practice exercises covering fundamental machine learning concepts from linear regression to CNNs.
What is Terry Um’s TensorFlow Exercises?
TensorFlow_Exercises is a collection of practice implementations covering fundamental machine learning algorithms using TensorFlow. It provides hands-on examples ranging from basic linear regression to convolutional neural networks, all implemented in Jupyter notebooks. The project serves as a practical learning resource for developers wanting to build TensorFlow proficiency through implementation.
Machine learning beginners and intermediate developers looking for structured TensorFlow practice materials. Data scientists and engineers who want to understand TensorFlow implementations of core algorithms through working examples.
Offers a curated progression of exercises that build from simple to complex models, with clean implementations focused on learning. Unlike official tutorials, it aggregates and organizes exercises from multiple quality sources into a single learning path.
Overview
The codes I made while I practiced various TensorFlow examples
Use Cases
Best For
- Learning TensorFlow basics through hands-on implementation
Related Projects
Found a gem we're missing?
Open-Awesome is built by the community, for the community. Submit a project, suggest an awesome list, or help improve the catalog on GitHub.
