Xiaoquan Kong is the author of Conversational AI with Rasa we got the chance to sit down with him and find out more about his experience of writing with Packt.
Q: What is/are your specialist tech area(s)?
Xiaoquan: TensorFlow, NLP, Chatbot, Python
Q: How did you become an author for Packt? Tell us about your journey. What was your motivation for writing this book?
Xiaoquan: One day, an editor from Packt Press contacted me and asked if I was interested in writing a Rasa book? In fact, before she contacted me, I had learned that many Rasa developers wanted a book to teach them how to efficiently use Rasa to develop chatbots and solve various pain points encountered in development. I want to help Rasa developers, so I gladly accepted Packt’s proposal.
Q: What kind of research did you do, and how long did you spend researching before beginning the book?
Xiaoquan: When I was studying for a master’s degree, my research topic was to use machine learning (deep learning was not popular at the time) to solve practical problems. After graduation, I have been engaged in the research and application of NLP/Chatbot for more than 5 years before writing this book. Among them, I have been using and contributing to Rasa for about three years.
Q: Did you face any challenges during the writing process? How did you overcome them?
Xiaoquan: During the writing process, the biggest challenge we encountered was that the Rasa version changed very quickly. We must regularly check our content and test our code to make sure it is still correct. This took us a lot of time, and we had to work overtime to catch up with the delivery schedule. This puts a lot of pressure on our psychology and physiology. But we have overcome this difficulty.
Q: What’s your take on the technologies discussed in the book? Where do you see these technologies heading in the future?
Xiaoquan: I think chatbots are very important. A chatbot is a human-centered application, which will become more and more important in the context of faster technological development and an increasingly aging population. Rasa is currently the leader in open-source chatbots and is likely to continue to lead. I personally think that the future development direction of Rasa will be to use more advanced technology but at the same time, the development process is getting simpler and simpler.
Q: Why should readers choose this book over others already on the market? How would you differentiate your book from its competition?
Xiaoquan: We are not worried about this. First of all, (as far as I know) our book is the first book about Rasa. We have no competitors yet. Secondly, this book is written by officially certified experts (Rasa Superhero & Rasa Hero) and contains many best practices and skills summarized from actual work, which is very helpful to Rasa developers.
Q. What are the key takeaways you want readers to come away with from the book?
- Understand the architecture and basic underlying principles of the Rasa
- Learn how to quickly build a variety of different types of chatbots (such as task-oriented, FAQ-like, and knowledge graph-based)
- Know how to build and use custom components
- Understand how to debug and optimize Rasa applications
Q. What advice would you give to readers learning tech? Do you have any top tips?
Xiaoquan: If you are a junior developer, it is recommended that you read the official documentation thoroughly and understand the key concepts. If you already have some practical experience, I suggest you try to read the source code and understand the key steps.
Q. Do you have a blog that readers can follow?
Xiaoquan: Yes, I have a blog (https://blog.xiaoquankong.ai/) with some blog posts about Rasa. Although most of them are written in Chinese, Google Translate can help you overcome language barriers.
Q. Can you share any blogs, websites, and forums to help readers gain a holistic view of the tech they are learning?
Xiaoquan: Rasa’s official blog (https://blog.rasa.com/), official documentation website (https://rasa.com/docs/), and official forum (https://forum.rasa.com/) have great learning content.
Q. How would you describe your author journey with Packt? Would you recommend Packt to aspiring authors?
Xiaoquan: Packt’s editorial team is very efficient, and I would be happy to recommend Packt to other authors.
Q. Do you belong to any tech community groups?
Xiaoquan: I am active in the Google Developers (TensorFlow) community and the Rasa community. I have official titles in these communities: Google Developer Expert in Machine Learning and Rasa SuperHero.
Q. What are your favorite tech journals? How do you keep yourself up to date on tech?
Xiaoquan: In fact, I hardly read technical journals anymore. I basically learn about new technologies from technology news sites, technology blogs of major companies, GitHub, and friends.
Q. How did you organize, plan, and prioritize your work and write the book?
Xiaoquan: My current job rarely requires overtime. This gave me enough time to finish writing the book. Regarding the writing plan, Packt has a very complete and professional process. They help me make a plan and remind me to deliver it at the corresponding time. This is very useful for amateur writers.
Q. What is that one writing tip that you found most crucial and would like to share with aspiring authors?
Xiaoquan: Done is better than perfect. This is true for creative work.
Xiaoquan’s GitHub: https://github.com/howl-anderson
You can find Xiaoquan’s book on Amazon by following this link: Please click here