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