Chapter 13. Summary, conclusions, and beyond
This chapter covers
- Looking back at the high-level concepts and ideas about AI and deep learning
- A quick overview of the different types of deep-learning algorithms we’ve visited in this book, when they are useful, and how to implement them in TensorFlow.js
- Pretrained models from the ecosystem of TensorFlow.js
- Limitations of deep learning as it currently stands; and an educated prediction for trends in deep learning that we will see in the coming years
- Guidance for how to further advance your deep-learning knowledge and stay up-to-date with the fast-moving field
This is the final chapter of this book. Previous chapters have been a grand tour of the current landscape of deep learning, enabled by the vehicles of TensorFlow.js and your own hard work. Through this journey, you have hopefully gained quite a few new concepts and skills. It is time to step back and look at the big picture again, as well as get a refresher on some of the most important concepts you’ve learned. This last chapter will summarize and review core concepts while expanding your horizons beyond the relatively basic notions you’ve learned so far. We want to make sure you realize this and are properly equipped to take the next steps of the journey on your own.