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Eat TensorFlow 2 in 30 Days is an open-source educational project that teaches developers how to build and train deep learning models using TensorFlow 2. It organizes learning materials into a structured curriculum designed to progressively introduce essential TensorFlow concepts and APIs. The tutorials cover tensors, automatic differentiation, computational operations, and neural network development. Users learn how to construct models with Keras and implement custom training workflows using lower-level TensorFlow APIs. The project also explains model evaluation, optimization, callbacks, and training with GPU and TPU hardware. Advanced lessons explore model deployment through TensorFlow Serving and integration with external systems. Practical examples and accessible explanations help learners apply TensorFlow to real machine learning problems.
Features
- Structured TensorFlow 2 Learning Curriculum
- Tensor Operations and Automatic Differentiation
- Keras Model Building and Training
- Custom Training Loops and Optimization
- GPU, Multi-GPU, and TPU Training Guides
- TensorFlow Serving Deployment Tutorials
Project Samples
