Lilly Tech Systems
Learn TensorFlow & Keras
Master Google's industry-standard deep learning framework. From tensors and neural networks to CNNs, NLP, and production deployment — build real AI models with TensorFlow 2 and the Keras API.
Your Learning Path
Follow these lessons in order, or jump to any topic that interests you.
1. Introduction
What is TensorFlow? Its history, TF2 vs TF1, eager execution, and the Keras API integration.
2. Getting Started
Install TensorFlow, understand tensors and operations, and build your first machine learning model.
3. Neural Networks
Sequential and Functional APIs, layers, training loops, callbacks, and model evaluation.
4. CNNs & Computer Vision
Conv2D layers, pooling, image classification, transfer learning, and TensorFlow Hub.
5. NLP with TensorFlow
Text preprocessing, word embeddings, RNNs, and building Transformers with TensorFlow.
6. Best Practices
Performance optimization, debugging, deployment strategies, and production-ready TF patterns.
What You'll Learn
By the end of this course, you'll be able to:
Build Neural Networks
Design, train, and evaluate deep learning models using the Keras Sequential and Functional APIs.
Classify Images
Build CNNs for computer vision tasks, use transfer learning with pre-trained models from TF Hub.
Process Text
Implement NLP pipelines using embeddings, RNNs, and Transformer architectures in TensorFlow.
Deploy Models
Export models with SavedModel format, serve with TF Serving, and optimize for production use.