1. You're done!
If you've finished the whole course you've probably put a lot of energy and work into understanding all of these new concepts, so
2. Congratulations!
congratulations! I hope you had fun! Now you have a better understanding of many key points when it comes to building a variety of neural networks and what you can use them for!
3. You've learned a lot
You've learned a lot! You completed 44 exercises and 14 lessons, you should be proud! You have a lot of power in your hands.
4. What you've learned
You've learned the basics of neural networks.
Built sequential models and learned to solve regression, binary classification, multi-class and multi-label problems with neural networks.
You've explored activation functions and carried out hyperparameter tuning, turning your keras models into sklearn estimators.
You've used autoencoders and de-noised images with them. You've learned key concepts about CNN networks and used the pre-trained resnet50 model to classify images.
You visualized convolutions for the MNIST dataset.
You learned about LSTMs concepts and worked with text and embedding layers.
You've used a lot of different datasets along the way also learning a lot of keras utility functions.
5. What could you learn next?
To keep on improving your understanding and learning on neural networks you should go deeper into CNNs, there's an specific course here on Datacamp.
You can also go deeper into LSTMs, there's a lot more to learn.
You could also check how to work with the Keras functional API which allows you to build more powerful models with shared layers and several branches.
And finally, consider getting creative with Generative Adversarial Networks and taking on some Deeplearning projects of your own.
6. Goodbye!
If you liked this course consider spreading the word so other people can also experience your journey! And feel free to give me a follow on Twitter or LinkedIn if you'd like.
And remember, your adventures with neural networks just begun, have a good one!
7. Have a good one!
¡Hasta la vista!