Summary

In this chapter, we briefly covered the features and capabilities of some other popular deep learning frameworks, libraries, and platforms. We started with Hugging Face, a popular framework for NLP. Then we explored OpenAI’s GPT-3 and DALL-E 2, both very powerful frameworks. The GPT-3 API can be used for a variety of NLP-related tasks, and DALL-E 2 uses GPT-3 to generate images from textual descriptions. Next, we touched on the PyTorch framework. According to many people, PyTorch and TensorFlow are equal competitors, and PyTorch indeed has many features comparable to TensorFlow. In this chapter, we briefly talked about some important features like the NN module, Optim module, and Autograd module of PyTorch. We also discussed ONNX, the open-source format for deep learning models, and how we can use it to convert the model from one framework to another. Lastly, the chapter introduced H2O and its AutoML and explain modules.

In the next chapter, we will learn about...