Curriculum
- 3 Sections
- 26 Lessons
- 20 Hours
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- Week 1: Introduction to Deep LearningLesson Content -13
- 1.1Understanding Neural Networks
- 1.2Deep Neural Network Architectures
- 1.3Introduction to TensorFlow and Keras
- 1.4Training a Deep Neural Network
- 1.5Gradient-based Optimisation
- 1.6Chaining Derivatives and Backpropagation
- 1.7Loss Functions, Optimizers, Initializers
- 1.8Batch-normalization
- 1.9Dropouts
- 1.10Understanding Image Data
- 1.11Understanding the Convolution Layer
- 1.12Filters and Feature Maps
- 1.13Pooling Layer
- Week 1-2: CNN ArchitecturesLesson Content -9
- Week 3: Object DetectionLesson Content -4
Semantic Segmentation
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