Keras Training and Certification in San Francisco, USA

This course provides a comprehensive introduction to Keras, a high-level deep learning API that runs on top of TensorFlow. Participants will learn how to build, train, and deploy deep learning models using Keras, covering fundamental concepts like neural networks, activation functions, optimization techniques, and model evaluation. The course includes hands-on exercises with real-world datasets to help participants gain practical experience.

Introduction to Keras and Deep Learning

• Overview of deep learning and neural networks
• Introduction to Keras and TensorFlow backend
• Setting up the Keras environment
• Understanding Keras models (Sequential vs. Functional API)

Training and Optimizing Keras Models

• Working with activation functions (ReLU, Sigmoid, Softmax, etc.)
• Understanding loss functions and optimization techniques (SGD, Adam, RMSprop)
• Evaluating and fine-tuning deep learning models
• Handling overfitting with dropout and batch normalization

Advanced Topics and Model Deployment

• Implementing Recurrent Neural Networks (RNNs) and LSTMs for sequential data
• Transfer learning and fine-tuning pre-trained models (VGG, ResNet, MobileNet)
• Saving and loading Keras models for future use
• Deploying Keras models using TensorFlow Serving and ONNX
• Hands-on: Developing and deploying an end-to-end deep learning model