Introduction to Deep Learning & Neural Networks with Keras
Completed by Sean Dickerson Springer
May 18, 2020
10 hours (approximately)
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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: Convolutional Neural Networks
- Category: Artificial Neural Networks
- Category: Machine Learning
- Category: Model Training
- Category: Model Optimization
- Category: Recurrent Neural Networks (RNNs)
- Category: Autoencoders
- Category: Keras (Neural Network Library)
- Category: Regression Analysis
- Category: Deep Learning
- Category: Transfer Learning