Introduction to Deep Learning & Neural Networks with Keras
Completed by Ming-Hua Sean Diep Lawrence
March 10, 2024
10 hours (approximately)
Ming-Hua Sean Diep Lawrence'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: Applied Machine Learning
- Category: Regression Analysis
- Category: Artificial Neural Networks
- Category: Machine Learning
- Category: Model Optimization
- Category: Image Analysis
- Category: Model Training
- Category: Natural Language Processing
- Category: Deep Learning
- Category: Convolutional Neural Networks
- Category: Transfer Learning
- Category: Recurrent Neural Networks (RNNs)
