Deep Learning in Theory and Practice (HU0F0S) – Details

Detaillierter Kursinhalt

Module 1 A Gentle Introduction to Deep Learning

• History of deep learning • Ethics in AI
• Overview of deep learning
• A single neuron
• What is a transfer function?

Module 2 Introduction to TensorFlow

• Introduction to TensorFlow
• The TensorFlow architecture
• TensorFlow data

Module 3 Introduction to Keras

• Introduction to Keras
• The Keras architecture
• Keras models
• Keras sequential vs functional API
• Keras layers
• Keras core modules

Module 4 Overfitting and Underfitting

• Overfitting and underfitting
• How to avoid

Module 5 Activation, Loss and Optimizer Functions

• Activation functions
• Loss functions
• Optimization functions

Module 6 Regularizing a Model & Hyperparameter Optimization

• Why regularize?
• Regularization types
• Hyperparameters
• Optimization techniques

Module 7 Pooling and Convolutions

• Convolutions
• Pooling in neural networks

Module 8 Big Data Deep Learning

• The big data perspective
• The big data deep learning team and roles
• Apache Spark
• Databricks
• Determined AI
• HPE Ezmeral