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Project includes an AI contextual chatbot built using the tensorflow and tflearn library. Used concepts of Natural Language Processing (NLP) and Neural Network.

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Vedant-S/AI-chatbot-cybersecurity

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AI Cybersecurity Chatbot:


Built an AI contextual chatbot using the tensorflow and tflearn library. Used concepts of Natural Language Processing (NLP) and Neural Network to build it. The intents file is used for training.


Dependencies:

1. pip3 install nltk
2. pip3 install tensorflow==1.13.2
3. pip3 install numpy
4. pip3 install tflearn
5. pip3 install random
6. pip3 install json

Use Cases:

One of the best application of integration of AI and Automation would be Chatbots. Chatbots are heavily used now-a-days. Usecases are listed below.

1. Saves labour work.
2. Provides 24x7 support.
3. Instant service.
4. Easy Communication.

Procedure to Run:

To run this application use jupyter notebook. Run each cell of notebook. Proceed with calling response() method and put your query within it.
for eg :

  • response("What services do you provide?")

This chatbot is primarly focused for a CyberSecurity based Industry. It can be a customer care Chatbot by using which you can know what kind of services does the Cyber Industry provide. Also you can use this chatbot to know some basic terminologies in Cyber Industry like:

  • What is cryptography ?
  • What is Hashing ?, etc.

Through use of Flask or similar technologies this chatbot can be embeeded in a website and the intent file can be edited as per requirement, to enhace the performance of the website.


Author:


+ Vedant Shrivastava | vedantshrivastava466@gmail.com

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Project includes an AI contextual chatbot built using the tensorflow and tflearn library. Used concepts of Natural Language Processing (NLP) and Neural Network.

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