Generating an effective and comprehensive introduction to two of the most transformative AI frameworks, namely GANs and Transformers, this e-book is a valuable resource for any AI enthusiast. With these models, readers will be able to know how they operate, their features, how they can be applied, and how to use them in AI-oriented projects.
In this E-Book, you will learn:
- Fundamentals of GANs: Through reading this chapter, the readers get familiar with the basic structure of GANs, generators, and discriminators, the training process based on the adversarial game, the loss functions used, and methods to make the training process more stable.
- GAN Applications and Use Cases: In general, the e-book covers various fields of GAN usage such as image and video synthesis, image translation, data augmentation, recommendation systems, etc. Examples from practice can prove useful to demonstrate the abilities of such forms.
- Introducing the Transformer Architecture: By the end of the article, readers can gain an understanding of the basic ideas of the Transformer framework, such as the encoder-decoder framework that allows for learning long-distance dependencies as well as multi-headed selfattention, and positional encodings.
- Transformers for NLP: In addition to pieces that have inspired new methods of natural language processing, including BERT, GPT-3, T5, and others, the book also includes code samples.
- Leveraging GANs and Transformers: This e-book explains how to train, evaluate, and implement GAN and Transformer models for different AI projects and it uses real-world examples.