5PM Deep Learning with Keras – Week 3 – Day 2
Welcome to Week 3, Day 2 of our Deep Learning with Keras course at 5PM! Today, we will be diving deeper into the world of neural networks and exploring more advanced techniques for building and training models.
Today’s Agenda:
- Review of Week 3, Day 1
- Introduction to Convolutional Neural Networks
- Hands-on Practice with CNNs in Keras
- Advanced Training Techniques
Review of Week 3, Day 1
Yesterday, we covered the basics of neural networks and how they can be used for image classification tasks. We discussed the structure of a neural network, the importance of activation functions, and how to train a model using Keras. Today, we will be building on this knowledge and exploring more complex architectures.
Introduction to Convolutional Neural Networks
Convolutional Neural Networks (CNNs) are a type of neural network that is well-suited for tasks such as image recognition and classification. CNNs use a special type of layer called a convolutional layer, which allows them to learn spatial hierarchies of features in an image. Today, we will be learning how to build and train a CNN in Keras.
Hands-on Practice with CNNs in Keras
During today’s session, you will have the opportunity to work on a hands-on coding exercise where you will build and train a CNN in Keras. This exercise will help reinforce the concepts we have covered so far and give you valuable experience in building and training neural networks.
Advanced Training Techniques
In addition to building a CNN, we will also be discussing some advanced training techniques that can help improve the performance of your models. These techniques include data augmentation, dropout regularization, and learning rate schedules. By implementing these techniques, you can make your models more robust and achieve better results.
Thank you for joining us for Week 3, Day 2 of our Deep Learning with Keras course at 5PM. We hope you find today’s session informative and engaging, and that you come away with a deeper understanding of neural networks and how to build and train them using Keras.
