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人工智能与数据科学基础.docx
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人工智能与数据科学基础.docx
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1
STUDY
MATERIAL
Foundation for AI and Data Science
•
15 MARKS IN Data Science [ DTSC ] ---- CLASS XI
2
Syllabus for Section 3 : Foundation for AI and Data science [ 15 Marks ] -
ARTI
•
History of AI : Alan Turing and cracking enigma , mark
1
machines ,
1
9
5
6
-
the birth of the term AI , AI winter of 70’s , expert systems of 1980s, skipped
journey of present day AI, pattern recognition and Machine learning
•
Brief History of Data Science , Data Science as a conjunction of computer
science statistics and domain knowledge . Definition of Data Science ,
Data Science Life Cycle – capture , maintain , process , analyze ,
communicate
•
Introduction to Linear Algebra and statistics for AI :
Basic matrix operations like matrix addition , subtraction , multiplication
, transpose of matrix , identity matrix.
Brief introduction to vectors , unit vector , normal vector , Euclidean
space.
Probability distribution , frequency , mean , median and mode , variance
and standard deviation , Gaussian distribution.
Correlation
,
Regression
,
parametric
,
non-parametric tests ( Basic idea )
Distance function , Euclidean norm , distance between two points in 2D
and 3D and extension of idea to n dimensions.
•
Basic ideas of different Data Science Toolkit : Excel , R
3
•
CONTENTS
Sl
No
Topic
Page No
1
AI-Basic Concept
4
2
History of AI
18
3
Turing Test
28
4
Data Science – Basic Concept
31
5
Distance function , Euclidean Norm ,
Distance between two points in 2D , 3D
and n dimension
35
6
Correlation and Regression
39
7
Uniform Distribution , parametric , non-
parametric
tests
52
8
Data Science Tool Kit
64
9
R
69
•
4
What Is Artificial Intelligence?
Artificial Intelligence is currently one of the hottest buzzwords in tech and with
good reason. The last few years have seen several innovations and
advancements that have previously been solely in the realm of science fiction
slowly transform into reality.
Experts regard artificial intelligence as a factor of production, which has the
potential to introduce new sources of growth and change the way work is done
across industries. China and the United States are primed to benefit the most
from the coming AI boom, accounting for nearly 70% of the global impact.
Artificial Intelligence is a method of making a computer, a computer-controlled
robot, or a software think intelligently like the human mind. AI is accomplished
by studying the patterns of the human brain and by analyzing the cognitive
process. The outcome of these studies develops intelligent software and
systems.
Weak AI vs. Strong AI
When discussing artificial intelligence (AI), it is common to distinguish between
two broad categories: weak AI and strong AI.
Weak AI (Narrow AI)
Weak AI refers to AI systems that are designed to perform specific tasks and are
limited to those tasks only. These AI systems excel at their designated functions
5
but lack general intelligence. Examples of weak AI include voice assistants like Siri
or Alexa, recommendation algorithms, and image recognition systems. Weak AI
operates within predefined boundaries and cannot generalize beyond their
specialized domain.
Strong AI (General AI)
Strong AI, also known as general AI, refers to AI systems that possess human-level
intelligence or even surpass human intelligence across a wide range of tasks.
Strong AI would be capable of understanding, reasoning, learning, and applying
knowledge to solve complex problems in a manner similar to human cognition.
However, the development of strong AI is still largely theoretical and has not been
achieved to date.
Types of Artificial Intelligence
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