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S.K.P ENGINEERING
COLLEGE
TIRUVANNAMALAI-606 611
SANTHIYA.T - 2ND YEAR CSE YOGESHWARI .K – 2ND YEAR CSE
ROLE OF DEEP
LEARNING AND DATA
SCIENCE IN CHATBOT
Here is where your presentation begins
HOW IT WORKS
01
04
CONCEPT OF DEEP
LEARNONG
CONCEPT OF DATA
SCIENCE
WHAT IS CHATBOT
ROLE OF DS AND DL
IN CHATBOT
DRAWBACKS
TABLE OF CONTENTS
02 03
05 06
08
07 APPLICATIONS
CONCLUSION
CONCEPT OF DEEP LEARNING:
īƒ˜Deep learning is the branch of machine learning which is based on
artificial neural network architecture.
īƒ˜In a fully connected Deep neural network, there is an input layer and
one or more hidden layers connected one after the other.
īƒ˜Deep Learning is a subfield of Machine Learning
that involves the use of deep neural networks to
model and solve complex problems.
HOW IT WORKS??
īƒ˜Deep learning networks learn by discovering intricate structures in the
data they experience.
īƒ˜By building computational models that are composed of multiple
processing layers, the networks can create multiple levels of abstraction to
represent the data.
CONCEPT OF DATA SCIENCE:
īƒ˜Data science is the study of data to extract meaningful insights for business.
īƒ˜Data: It refers to the raw informationthat is collected, stored, and
processed.
īƒ˜Science: It refers to the systematic study and investigation of phenomena
using scientific methods and principles.
HOW IT WORKS??
īƒ˜It is a multidisciplinary approach that combines principles and practices
from the fields of mathematics, statistics, artificial intelligence,etcâ€Ļ,to analyze
large amounts of data.
WHAT IS CHATBOT:
īƒ˜A chatbot is a computer program that simulates
human conversation through voice commands or
text chats or both.
īƒ˜Chatbot, short for chatterbox, is an artificial
intelligence (AI) feature that can be embedded and
used through any major messaging application.
HOW CHATBOT WORKS:
TYPES OF CHATTBOT:
MENU BASED
CHATBOTS
VOICE BOTS
MESSAGE BASED
CHATBOTS
KEYBOARD
CHATBOTS
HYBRID
CHATBOTS
SKILL BASED
ROLE OF DATA SCIENCE AND DEEP
LEARNING IN CHATBOT:
īƒ˜A deep learning chatbot learns right
from scratch through a process called
“Deep Learning.” In this process, the
chatbot is created using machine
learning algorithms.
īƒ˜Data Analytics helps chatbots
collect and store vast amounts of user
interaction data, including text
conversations, voice recordings, and
user preferences.
īƒ˜Specifically
on healthcare provider
websites, insurance
chatbots can act as a
24/7.
īƒ˜Integrating a chatbot
with the classroom is
essential for a big leap
in the education
īƒ˜ chatbots to book
their travels for them,
instead of doing it
manually.
īƒ˜IBM's conversational AI
software is called
IBM Watson Conversation.
HEALTHCARE EDUCATION TRAVEL WATSON
ASSISTANT
CHATBOT
IMPORTANT APPLICATIONS:
MAIN DRAWBACKS:
īƒ˜Chatbots Are Often
Repetitive.
īƒ˜chatbots have no emotions
īƒ˜Customers Could Become
Frustrated
īƒ˜Absence of human
connection.
īƒ˜Data Security.
īƒ˜Less Understanding
of Natural Language
īƒ˜Limited Functionality.
īƒ˜Needs high
maintenance
īƒ˜They Lose Customer
Insights
CONCLUSION:
īƒ˜In conclusion, chatbots are defined as computer programs
that simplify information retrieval and problem solving using
natural language, thus enhancing customer service and
relationship quality.
THANK YOU ALL!

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CHATBOT USING DEEP LEARNING AND DATA SCIENCE

  • 1. S.K.P ENGINEERING COLLEGE TIRUVANNAMALAI-606 611 SANTHIYA.T - 2ND YEAR CSE YOGESHWARI .K – 2ND YEAR CSE
  • 2. ROLE OF DEEP LEARNING AND DATA SCIENCE IN CHATBOT Here is where your presentation begins
  • 3. HOW IT WORKS 01 04 CONCEPT OF DEEP LEARNONG CONCEPT OF DATA SCIENCE WHAT IS CHATBOT ROLE OF DS AND DL IN CHATBOT DRAWBACKS TABLE OF CONTENTS 02 03 05 06 08 07 APPLICATIONS CONCLUSION
  • 4. CONCEPT OF DEEP LEARNING: īƒ˜Deep learning is the branch of machine learning which is based on artificial neural network architecture. īƒ˜In a fully connected Deep neural network, there is an input layer and one or more hidden layers connected one after the other. īƒ˜Deep Learning is a subfield of Machine Learning that involves the use of deep neural networks to model and solve complex problems.
  • 5. HOW IT WORKS?? īƒ˜Deep learning networks learn by discovering intricate structures in the data they experience. īƒ˜By building computational models that are composed of multiple processing layers, the networks can create multiple levels of abstraction to represent the data.
  • 6. CONCEPT OF DATA SCIENCE: īƒ˜Data science is the study of data to extract meaningful insights for business. īƒ˜Data: It refers to the raw informationthat is collected, stored, and processed. īƒ˜Science: It refers to the systematic study and investigation of phenomena using scientific methods and principles.
  • 7. HOW IT WORKS?? īƒ˜It is a multidisciplinary approach that combines principles and practices from the fields of mathematics, statistics, artificial intelligence,etcâ€Ļ,to analyze large amounts of data.
  • 8. WHAT IS CHATBOT: īƒ˜A chatbot is a computer program that simulates human conversation through voice commands or text chats or both. īƒ˜Chatbot, short for chatterbox, is an artificial intelligence (AI) feature that can be embedded and used through any major messaging application.
  • 10. TYPES OF CHATTBOT: MENU BASED CHATBOTS VOICE BOTS MESSAGE BASED CHATBOTS KEYBOARD CHATBOTS HYBRID CHATBOTS SKILL BASED
  • 11. ROLE OF DATA SCIENCE AND DEEP LEARNING IN CHATBOT: īƒ˜A deep learning chatbot learns right from scratch through a process called “Deep Learning.” In this process, the chatbot is created using machine learning algorithms. īƒ˜Data Analytics helps chatbots collect and store vast amounts of user interaction data, including text conversations, voice recordings, and user preferences.
  • 12. īƒ˜Specifically on healthcare provider websites, insurance chatbots can act as a 24/7. īƒ˜Integrating a chatbot with the classroom is essential for a big leap in the education īƒ˜ chatbots to book their travels for them, instead of doing it manually. īƒ˜IBM's conversational AI software is called IBM Watson Conversation. HEALTHCARE EDUCATION TRAVEL WATSON ASSISTANT CHATBOT IMPORTANT APPLICATIONS:
  • 13. MAIN DRAWBACKS: īƒ˜Chatbots Are Often Repetitive. īƒ˜chatbots have no emotions īƒ˜Customers Could Become Frustrated īƒ˜Absence of human connection. īƒ˜Data Security. īƒ˜Less Understanding of Natural Language īƒ˜Limited Functionality. īƒ˜Needs high maintenance īƒ˜They Lose Customer Insights
  • 14. CONCLUSION: īƒ˜In conclusion, chatbots are defined as computer programs that simplify information retrieval and problem solving using natural language, thus enhancing customer service and relationship quality.