Course 1 of the Deep Learning Specialization. Covers the foundations of deep learning, including neural network architecture, forward and backward propagation, and building deep neural networks.
Cert Category: Deep Learning
Sequence Models
Course 5 of the Deep Learning Specialization. Covers RNNs, GRUs, LSTMs, attention mechanisms, and transformer networks.
Convolutional Neural Networks
Course 4 of the Deep Learning Specialization. Covers CNN architectures, object detection, face recognition, and neural style transfer.
Structuring Machine Learning Projects
Course 3 of the Deep Learning Specialization. Covers ML strategy, error analysis, and techniques for building successful machine learning projects.
Hyperparameter Tuning, Regularization and Optimization
Course 2 of the Deep Learning Specialization. Covers optimization algorithms, hyperparameter tuning, batch normalization, and programming frameworks.
Deep Learning Specialization
The Deep Learning Specialization is a foundational program that teaches the capabilities, challenges, and consequences of deep learning and prepares learners to participate in the development of leading-edge AI technology.
This specialization consists of five courses covering neural networks, deep learning optimization, structuring ML projects, convolutional neural networks, and sequence models.
