- Keras (Neural Network Library)
- Network Architecture
- Network Model
- Artificial Neural Networks
- Natural Language Processing
- Tensorflow
- Image Analysis
- Regression Analysis
- Machine Learning
- Machine Learning Methods
- Computer Vision
- Deep Learning
Introduction to Deep Learning & Neural Networks with Keras
Completed by RAPHAEL CHUKWUBELIJE MADU
July 2, 2021
10 hours (approximately)
RAPHAEL CHUKWUBELIJE MADU'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
