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:
īDeep learning is the branch of machine learning which is based on
artificial neural network architecture.
īIn a fully connected Deep neural network, there is an input layer and
one or more hidden layers connected one after the other.
īDeep 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??
īDeep learning networks learn by discovering intricate structures in the
data they experience.
īBy 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:
īData science is the study of data to extract meaningful insights for business.
īData: It refers to the raw informationthat is collected, stored, and
processed.
īScience: It refers to the systematic study and investigation of phenomena
using scientific methods and principles.
7. HOW IT WORKS??
īIt is a multidisciplinary approach that combines principles and practices
from the fields of mathematics, statistics, artificial intelligence,etcâĻ,to analyze
large amounts of data.
8. WHAT IS CHATBOT:
īA chatbot is a computer program that simulates
human conversation through voice commands or
text chats or both.
īChatbot, 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:
īA deep learning chatbot learns right
from scratch through a process called
âDeep Learning.â In this process, the
chatbot is created using machine
learning algorithms.
īData Analytics helps chatbots
collect and store vast amounts of user
interaction data, including text
conversations, voice recordings, and
user preferences.
12. īSpecifically
on healthcare provider
websites, insurance
chatbots can act as a
24/7.
īIntegrating a chatbot
with the classroom is
essential for a big leap
in the education
ī chatbots to book
their travels for them,
instead of doing it
manually.
īIBM's conversational AI
software is called
IBM Watson Conversation.
HEALTHCARE EDUCATION TRAVEL WATSON
ASSISTANT
CHATBOT
IMPORTANT APPLICATIONS:
13. MAIN DRAWBACKS:
īChatbots Are Often
Repetitive.
īchatbots have no emotions
īCustomers Could Become
Frustrated
īAbsence of human
connection.
īData Security.
īLess Understanding
of Natural Language
īLimited Functionality.
īNeeds high
maintenance
īThey Lose Customer
Insights
14. CONCLUSION:
īIn conclusion, chatbots are defined as computer programs
that simplify information retrieval and problem solving using
natural language, thus enhancing customer service and
relationship quality.