- Computer Vision
- Machine Learning Methods
- Regression Analysis
- Deep Learning
- Network Architecture
- Keras (Neural Network Library)
- Image Analysis
- Tensorflow
- Artificial Neural Networks
- Network Model
- Natural Language Processing
- Machine Learning
Introduction to Deep Learning & Neural Networks with Keras
Completed by MARC YVES R BUEKENHOUT
July 27, 2021
10 hours (approximately)
MARC YVES R BUEKENHOUT'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
