Module 1: Introduction to Deep Learning
- Introduction to deep learning trends and applications
- Examples of deep learning applications
Module 2: Neural Network Basics
- Machine learning problem setup and neural network mindset
- Vectorization for efficient computation
Module 3: Shallow Neural Network
- Building a neural network with one hidden layer
- Understanding forward propagation and backpropagation
Module 4: Deep Neural Network
- Computation in deep learning
- Building and training deep neural networks for computer vision tasks
Module 5: Practical Aspects of Deep Learning
- Initialization methods for deep neural networks
- Regularization techniques to prevent overfitting
Module 6: Optimization Algorithms
- Advanced optimization techniques for neural networks
- Random minibatching and learning rate decay
Module 7: Hyperparameter Tuning, Batch Normalization, Frameworks
- Introduction to the TensorFlow framework
- Training neural networks on TensorFlow datasets
Module 8: ML Strategy
- Strategic guidelines for setting goals and managing ML production workflow
- Error analysis procedures
Module 9: Foundations of Convolutional Neural Networks
- Understanding pooling and convolutional layers
- Building deep CNNs for image classification
Module 10: Deep Convolutional Models: Case Studies
- Exploring advanced tricks and methods in deep CNNs
- Applying transfer learning to pretrained models
Module 11: Object Detection
- Using CNNs for object detection tasks
Module 12: Face Recognition & Neural Style Transfer
- Applying CNNs for face recognition tasks
- Implementing neural style transfer for art generation
Module 13: Recurrent Neural Networks
- Introduction to recurrent neural networks (RNNs)
- Variants of RNNs for sequential data modeling
Module 14: Natural Language Processing & Word Embeddings
- NLP applications with deep learning models
- Word embeddings for text analysis
Module 15: Sequence Models & Attention Mechanism
- Enhancing sequence models with attention mechanisms
- Speech recognition and audio data processing
Module 16: Transformer Network
- Understanding the functioning of transformer networks