TensorFlow Tutorial with Examples.
TensorFlow tutorial for deep learning with Keras: layers, training loops, custom models and TFX deployment pipelines.
Beginner
Start here — no prior experience needed
TensorFlow Learning Roadmap
A structured path through TensorFlow and Keras — from your first model to production deployment on mobile, server, and cloud.
Introduction to TensorFlow and Keras
Learn TensorFlow tensors, GradientTape, and Keras 3 through runnable examples: train an MNIST classifier, a functional model, and a custom training loop.
TensorFlow Projects
Projects covering TensorFlow and Keras from basic neural networks to production serving — building real models that solve real problems.
Intermediate
For developers with core concepts down
TensorFlow CNNs and Transfer Learning
Build Keras CNNs step by step: conv shapes, weight sharing, a Fashion-MNIST model on CPU, then transfer learning and fine-tuning MobileNetV2 on flowers.
TensorFlow RNNs and LSTMs
Build Keras sequence models with LSTM and GRU: output shapes, TextVectorization, masking, IMDB sentiment on CPU, and forecasting against a naive baseline.
Advanced
Production-grade patterns for experienced engineers
TensorFlow Model Deployment
Deploy a Keras model for real: export a SavedModel, serve it with TF Serving in Docker, wrap it in FastAPI, and convert it to int8 TFLite run with LiteRT.
TensorFlow Transformers and KerasHub
Build Transformers in Keras from attention up: masks, position embeddings, an encoder trained on IMDB, and the KerasHub BERT tokenizer and classifier API.