You're done!

Introduction to Deep Learning with Keras

Miguel Esteban

Data Scientist & Founder

Congratulations!

You've learned a lot

What you've learned

• The basics of neural networks
• Building sequential models
• Building models for regression
• Approaching binary classification, multi-class and multi-label problems with neural networks
• Activation functions
• Hyperparameter tuning
• Autoencoders

• De-noising images
• CNN concepts
• Use pre-trained models
• Visualize convolutions
• LSTMs concepts
• Work with embedding layers and text
• All of this by using many different datasets and learning plenty of Keras's utility functions.

What could you learn next?

• Go deeper into CNNs
• Go deeper into LSTMs
• Keras Functional API
• Models that share layers, models with several branches
• GANs: Generative Adversarial Networks
• Deeplearning projects

Have a good one!

Introduction to Deep Learning with Keras