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Building chatbots with Python : using natural language processing and machine learning /
Build your own chatbot using Python and open source tools. This book begins with an introduction to chatbots where you will gain vital information on their architecture. You will then dive straight into natural language processing with the natural language toolkit (NLTK) for building a custom langua...
| Clasificación: | Libro Electrónico |
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| Autor principal: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
[New York, New York] :
Apress,
[2019]
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| Temas: | |
| Acceso en línea: | Texto completo (Requiere registro previo con correo institucional) |
Tabla de Contenidos:
- Chapter 1: Introducing Chatbots Chapter Goal: Make the user get familiar with Chatbots. Sub -Topics1. Do's and Don'ts in Chatbots2. What are the limitations of chatbots and how we should solve them?3. What are different kind of chatbots? Where do they fit in? Chapter 2: Natural Language Processing Chapter Goal: Be able to do custom natural language processing platform for your chatbotsSub
- Topics 1. Installation of NLTK and methods in natural language processing. 2. POS Tagging, Stemming, Lemmetization, 3. Logical SemanticsChapter 3: Chatbot DevelopmentChapter Goal: Building a chatbot and defining its data constraintsSub
- Topics: 1. Using api.ai platform to create a chatbot2. Feeding data and defining Intents and entities Chapter 4: Chatbot Communication Chapter Goal: Enabling communication with the bot to make the bot respond to your queries. Sub
- Topics: 1. Making our chatbot respond to our queries2. Integration and Deployment Chapter 5: Build-Train-Deploy Chapter Goal: To build, train and deploy a chatbot of your own Sub
- Topics: 1. Getting acclimatize to use open source libraries to train your data2. Defining Intents and entities on your data3. Using ML algorithms to predict the intent and take action based on that4. Using your code in a web app to make a conversational agent. 5. Deploy your app on your own server with AWS.