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上課地點(diǎn)：【上?！浚和瑵?jì)大學(xué)(滬西)/新城金郡商務(wù)樓(11號(hào)線白銀路站) 【深圳分部】：電影大廈(地鐵一號(hào)線大劇院站)/深圳大學(xué)成教院 【北京分部】：北京中山學(xué)院/福鑫大樓 【南京分部】：金港大廈(和燕路) 【武漢分部】：佳源大廈（高新二路） 【成都分部】：領(lǐng)館區(qū)1號(hào)（中和大道） 【廣州分部】：廣糧大廈 【西安分部】：協(xié)同大廈 【沈陽(yáng)分部】：沈陽(yáng)理工大學(xué)/六宅臻品 【鄭州分部】：鄭州大學(xué)/錦華大廈 【石家莊分部】：河北科技大學(xué)/瑞景大廈
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| 課時(shí) |
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☆課程大綱☆ |
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- Introduction to ChatBots
- Overview of Conversational Software
- Building Your First Basic ChatBot
- Setting Up Your ChatBot to Receive Text and Respond to Users
Adding the Basic Elements of Personality
Teaching Your ChatBot to Answer Basic Questions
Adding Variety to Your ChatBot's Responses
Making Your ChatBot Ask Questions
Building Rule-Based Systems for Parsing Text
Using Machine Learning to Turn Natural Language into Structured Data for Your ChatBot
- Overview of SpaCy, Scikit-learn, and Rasa NLU
Installing and Configuring SpaCy, Scikit-learn, and Rasa NLU
Intents and Entities and their Classifications
Natural Language Processing Fundamentals Theory Refresher
Building Models from Real-World Sentences Using the ATIS Dataset
Building Your Virtual Assistant ChatBot
- Overview of a Virtual Assistant
Working with SQL in Python
Teaching Your ChatBot to Access Data from a Database
Writing Queries from Parameters
Building a Database from Natural Language
Implementing Custom Virtual Assistant Features on Your ChatBot
Answering Specific Queries through Database Access
Refining Search, Performing Basic Negation, and Filtering Data
Making Your ChatBot Stateful: Keeping Track of States of Interaction for Better ChatBot Dialogs
- Performing Basic Actions
Asking Contextual Questions and Queuing Answers
Dealing with Rejection
Testing and Deploying Your ChatBot
- Troubleshooting
- Summary and Conclusion
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