The document discusses the critical role of mathematics in artificial intelligence (AI) and machine learning, highlighting that they are interconnected branches essential for designing algorithms. It emphasizes key mathematical concepts such as linear algebra, calculus, probability, and statistics that underpin the functioning of AI tools and models. Mastery of these mathematical principles is essential for anyone pursuing a career in AI or related fields.

1. MATHEMATICAL
ARTIFICIAL INTELLIGENCE
.
Group9
1.Adithi R
2.Ananya Gowda
3.Chethan S
4. Kavya .s
5.Likitha K
6..Venkatesh

2. MATHEMATICAL ARTIFICIAL INTELLIGENCE.
INTRODUCTION
• Artificial Intelligenceand Machine Learning are the
branches of engineering in which mathematics and
science are fundamental.
• Artificial Intelligenceslowly became a part of our lives.
Before we could realize, AI has become a necessity.
• We were alreadydependent on it for every other thing
in our life.
• In the learning of Mathematicsand AI, it often appears
as disconnected areas whereas they are two necessary
branches of the same tree.
• Either of them alone produces only ethereal structures,
or routines and ad-hoc/emergence programs.

3. • Mathematics plays an important role as it buildsthe foundationfor
programming.
• The theories are used to make assumptionsabout the underlyingdata
when we are designing these deep learning or AI algorithms
• . It is important for us to understandthe key probability distributions.
Machinelearning is powered by four critical concepts and is
Statistics, Linear Algebra, Probability,and Calculus.

4. Why is Mathematics Vital to Thrive
In Your AI Career?
• The future we have seen in sciencefictionmoviesis here.
From virtual reality to functionalgadgets,AI has invaded
our lives in ways that no one has ever seen or expected
before.
• AI tools and chatbots have been on the verge of
a breakthrough in the promptly-evolvingtechrealm.

5. How is AI connected with mathematics?
• So how doesAI work? Is it
any sort of rocket science?No,
it isn’t.
• It’s all about the integration
of mathematicalconceptsinto
Programmingto give the
output that mimicshuman
behavior.
• It’s more of a combinationof
mathematicsandAI
rather than just being some
sort of sciencefiction.

6. • Artificial intelligenceproblemsconstitute on two
general categories; Search Problems,
and RepresentationProblems.
• Followingthem are interconnectedmodels and
tools likeRules, frames, Logics,and Nets.
• All of them are very mathematicaltopics.
• The primarypurpose of Artificialintelligenceis
to create an acceptablemodelfor human
understanding.
• And these modelscan be prepared with the
ideas and strategies from various branchesof
Mathematics.

7. What kind of math is used in Artificial Intelligence?
• Behind allof the significantadvances,there is mathematics.
• The conceptsof LinearAlgebra,Calculus,game theory, Probability,statistics, advanced
logisticregressions,andGradientDescent are all major data scienceunderpinnings
• Math helps in understanding logical reasoning and attention to
detail. It enhances your abilities to think under pressure and
increase your mental endurance.
• Mathematical concepts give the real solution of hypothetical or
virtual problems.
• It is about structure, developing principles that remain true even if
you make any alteration in the components.

8. Linear algebra
Linearalgebra
LinearAlgebrais the fieldof applied mathematicswhich is somethingAI
experts can’t live without.You willnever become a goodAI specialistwithout mastering
this field.As SkylerSpeakmansaid,
“Linear Algebra is the mathematics
of the 21st century.”
• LinearAlgebrahelps in generatingnew ideas, that’s why it is a
must-learn thing forAI scientistsand researchers.
• They can abstract data and models with the conceptsof scalars,
vectors,Tensors, matrices, sets and sequences,Topology,Game
Theory, Graph theory, functions,linear transformations,
eigenvaluesand eigenvectors.

9. Vectors
• In linear programming, vectors are
used to deal with inequalities and
systems of equations for
notational conveniences.Artificial
Intelligence
scientists use different techniques of
vectors to solve problems of regression,
clustering, speech recognition, and
machine translation.
• The concepts are also used to store
the internal representations ofAI models
like linear classifiers and deep learning
networks.

10. Matrix theory
In science fiction movies, you usuallysee that
by performing some computational structure similar
to the neural system, a neuralnetwork has been
produced by generating the connectionsbetween
neurons to match the way of reasoning of a human
brain. The concept of Matrixis used in the study of
neural networks.​
A Non-Linear hypothesis can be done
in neural network by forming artificial
neurons in three layers
AI Scientists classify the neural networks
from their quantity of hidden layers and
the way they connect.
Real Neuron

11. Artificial Neuron
The neural
network can
be formed by
those
artificial neur
ons and it
took about 20
years to
discover this

12. Calculus
Differential calculus, Multivariate calculus,
Integral calculus, Error minimization and optimization
via gradient descent, Limits, Advanced logistic
regressions are all the concepts used in mathematical
modeling. A well-designed mathematical model is used
in Biomedical sciences to simulate complex
biological processes of human health and diseases with
high fidelity.

13. Let’s consider a Robot. A robot can only move
forward for a certain number of seconds, but not a
certain distance. To make the robot go forward,
scientists use mathematicsin its programming.
Discrete random variables,continuousrandom
variables,Bayes Formula, and normalizationare
some concepts of probability thatare used in
Roboticsnavigationand locomotionalong with
other concepts of linear algebra.

14. The Final Verdict
Whether you want to pursue a
career as a machine learning
engineer, data scientist, or a
robotic scientist, you need to
excel in
mathematics. Mathematics
can enhance analytical thinking
skillswhich are vital in Artificial
intelligence. AI scientists believe
that what people think about AI
is that, it is all magic, but
it isn’t magic, it’s the
mathematics that creates magic
behind all the inventions. So, to
lead in today’s AI-driven world,
you need to have a great flair in
math.....

15. Thank You