Practical Bot Development: Designing and Building Bots with Node.js and Microsoft Bot Framework
Szymon Rozga
654 pages, parution le 18/07/2018
Résumé
Practical Bot Development will teach you how to create your own bots on platforms like Facebook Messenger and Slack, incorporate extension APIs, and apply AI and ML algorithms in the cloud. By the end of this book, you'll be equipped with the information to reach thousands of new users with the bots you create!
The book is a great resource for those looking to harness the benefits of building their own bots and leveraging the platform feasibility of them.
What You'll Learn
- Understand the general architecture of a bot
- Distinguish between a great bot experience versus a bad bot experience.
- Explore the ideas behind natural language processing and apply them to bot development
- Implement real Messenger, Slack, and custom channel bots using Node.js and the Microsoft Bot Builder framework
- Deploy bots to Facebook Messenger and Slack
Engineers, hobbyists, and the design oriented community looking looking for an introduction to the technologies and concepts involved in building bots. The experience level could be from beginner to expert, although some familiarity with Node.js and APIs will be assumed.
- Motivation: apps vs bots and interacting with computers using Natural Language Interfaces. Google Now, Siri, Alexa. Great progress in recent years in both translation, voice recognition and natural language understanding technologies. Democratization of AI and Machine Learning APIs. Bots as a new way of implementing user interfaces.
- Use Case: describe a bot to help users order tickets
- Use it to describe the following concepts:
- Natural language recognition
- Text conversations
- Rich media conversations
- Bot-led conversations
- Human hand off
- Embedding into messaging apps
- Motivation: there is a good way for bots to communicate to you and there is a bad way. This chapter will distill some common "good" approaches to a bot and Also show some examples of bad communication.
- conversational User Experience
- Text vs rich conversations
- Bot initiated conversations
- Perceived performance
- Personalized content
- Concise and clear messaging
- Consistent voice
- Do one thing well, provide value
- Motivation: part of the reason bots are becoming a thing is that natural language recognition technologies are widely available and easier to use.
- Intent classification
- Entity Extractors - Named Entity Extraction
- LUIS
- How to create a model
- How to train LUIS to recognize intents and entities (use ticket ordering bot as a use case)
- Action Fulfillment - not used in LUIS anymore, but still used in cloud based, intent-led bot frameworks. It is interesting to know when creating bots.
- Motivation: cloud bot services vs bot as a web service models. We favor bot as a web service model for ease of use, control, extensibility etc.
- MSFT bot builder framework - what is it?
- Node.js and why we use the Node.js version vs the C# version
- Core concepts
- Intro to emulator
- Node.js samples
- How to run sample
- Some basic bot samples
- Motivation: we need to go over the different concepts inside the bot builder framework and how they help us build bots.
- Dialogs
- Messages
- Connector
- Channels
- Conversation State
- Recognizers
- Actions
- Proactive messages
- Motivation: Build a sample bot that uses all of the concepts in the previous chapter
- Back to ordering tickets bot - lots of coding
- Motivation: Expand sample from #6 with some more advanced concepts like proactive messaging, better dialog management, custom recognizers, deeper action support, group chats, etc.
- Lots of code here
- Motivation: a bot is useless unless it is connected to a channel. Let's see how this is done. We introduce the bot framework web site.
- Focus on Messenger and Slack
- Show some custom functionality such as messenger square cards or slack updating messages
- Motivation: sometimes you would like to support a custom channel that is not supported out of the box by Microsoft. How do we do this?
- Using direct line
- Using vanilla bot builder interfaces
- Motivation: there is a lot of easy to use AI/ML services out there. What are they and how can they help our bot be smarter.
- Vision
- Emotion
- Language Detection
- Sentiment
- Linguistic Analytics
- QnA Maker
- Why use these? Why not use these services? What is the goal of your bot?
- Motivation: rich content and graphics can better capture information than plain text using dynamically generated images
- Adaptive Cards - adaptivecards.io - one option, easier to deal with
- Custom HTML generation - generate images from html using PhantomJS on the server
- Motivation: customers want to keep in touch with your brand, what happens when a human is needed?
- How do we log data?
- What are the interesting measures that we look for in a bot?
- What systems are out there and what can they can us figure out about our customers and bots?
- Brief overview of the technology field: Api.ai, wit.ai, IBM conversation, amazon, etc.
- Goal of this chapter will be to demonstrate that these frameworks have very similar approaches in terms of NLU, conversation management, state, etc. Knowledge from this book will allow you to develop using the other systems.
Caractéristiques techniques
| PAPIER | |
| Éditeur(s) | Apress |
| Auteur(s) | Szymon Rozga |
| Parution | 18/07/2018 |
| Nb. de pages | 654 |
| EAN13 | 9781484235393 |
Avantages Eyrolles.com
Livraison à partir de 0,01 € en France métropolitaine
Paiement en ligne SÉCURISÉ
Livraison dans le monde
Retour sous 15 jours
+ d'un million et demi de livres disponibles
Consultez aussi
- Les meilleures ventes en Graphisme & Photo
- Les meilleures ventes en Informatique
- Les meilleures ventes en Construction
- Les meilleures ventes en Entreprise & Droit
- Les meilleures ventes en Sciences
- Les meilleures ventes en Littérature
- Les meilleures ventes en Arts & Loisirs
- Les meilleures ventes en Vie pratique
- Les meilleures ventes en Voyage et Tourisme
- Les meilleures ventes en BD et Jeunesse
