Here we will learn :
Libraries and Frameworks
Python Deep Learning – Introduction
Python Deep Learning – Environment
Python Deep Basic Machine Learning
Artificial Neural Networks
Deep Neural Networks
Python Deep Learning – Fundamentals
Training a Neural Network
Computational Graphs
Python Deep Learning – Applications
Python Deep Learning – Implementations
Curriculum
- 11 Sections
- 56 Lessons
- 10 Weeks
Expand all sectionsCollapse all sections
- Libraries and FrameworksIn this chapter, we will relate deep learning to the different libraries and frameworks.3
- Python Deep Learning - Introduction2
- Python Deep Learning - Environment2
- Python Deep Basic Machine Learning2
- Artificial Neural Networks3
- Deep Neural Networks8
- Python Deep Learning - Fundamentals4
- Training a Neural Network7
- Computational Graphs4
- Python Deep Learning - Applications2
- Python Deep Learning - Implementations19
- 11.1overview
- 11.2Step 1: Data preprocessing
- 11.3Step 2
- 11.4Step 3
- 11.5Step 4
- 11.6Step 5
- 11.7Step 6
- 11.8Step 7
- 11.9Step 8
- 11.10Step 9
- 11.11Step 10
- 11.12Step 11
- 11.13Step 12
- 11.14Step 13
- 11.15Step 14
- 11.16The Forward Propagation Algorithm
- 11.17The Rectified Linear Activation Function
- 11.18Applying the network to many Observations/rows of data
- 11.19Deep multi-layer neural networks
