The module focuses on deep learning concepts using different types of neural network implementation.

Neural Networks: Beginners to Advanced

This module is an accumulation of well-grounded knowledge and experience in deep learning. It provides you with the basic concepts you need in order to start working with and training various machine learning models. You will cover both basic and intermediate concepts including, but not limited to, convolutional neural networks, recurrent neural networks, generative adversarial networks as well as transformers. After completing this module, you will have a comprehensive understanding of the fundamental architectural components of deep learning. Whether you’re a data and computer scientist, computer and big data engineer, solution architect, or software engineer, you will benefit from this module.

Neural Networks to Deep Learning



Please take your time on each question, and make sure you understand why each answer is correct/incorrect. If you have any doubt, feel free to go back to the lessons and double-check.


Test the knowledge you acquired in this chapter by taking this mini-quiz on neural networks and their training process.

Learn Deep Learning

Neural Networks

Training Neural Networks

Convolutional Neural Networks

Recurrent Neural Networks

Autoencoders

Generative Adversarial Networks

Attention and Transformers

Graph Neural Networks

Conclusion

Quiz Yourself on Neural Networks