Introduction to Deep Learning & Neural Networks with Keras
Completed by Karam Mohammad Hammadeh
December 20, 2019
10 hours (approximately)
Karam Mohammad Hammadeh's account is verified. Coursera certifies their successful completion of Introduction to Deep Learning & Neural Networks with Keras
What you will learn
Describe the foundational concepts of deep learning, neurons, and artificial neural networks to solve real-world problems
Explain the core concepts and components of neural networks and the challenges of training deep networks
Build deep learning models for regression and classification using the Keras library, interpreting model performance metrics effectively.
Design advanced architectures, such as CNNs, RNNs, and transformers, for solving specific problems like image classification and language modeling
Skills you will gain
- Category: Autoencoders
- Category: Keras (Neural Network Library)
- Category: Regression Analysis
- Category: Model Optimization
- Category: Model Training
- Category: Network Architecture
- Category: Recurrent Neural Networks (RNNs)
- Category: Convolutional Neural Networks
- Category: Machine Learning Methods
- Category: Applied Machine Learning
- Category: Machine Learning
- Category: Image Analysis
