Artificial Intelligence and

Machine Learning (AI & ML )

Presented by;
RAGANI RANJAN. .
 Contents
01 Introduction to AI & ML
02 Career in AI & ML
03 Start ups to drive growth of AI & ML

04 Skills for success in AI & ML

05 Conclusions
I . Introduction to
AI

• AI is a branch of Science and assist machines to f ind

solutions to complex problems in a more human-like
fashion.

• Artif ic ial Intelligence is the future of Next Generation

Technology.

• It encompasses variety of disciplines like Medical,

Finance, Engineering.
AI is the main tool behind new-age Generalized AI is worth thinking
innovation and discove rie s like about be cause it stre tche s our
driverless cars or disease detecting imaginations and it gets us to think
algorithm about our core values and issues of
choice

We are now solving problems with

Artificial Intelligence will be ‘vastly m a ch in e le a rn in g a n d A I t h a t
smarter’ than any human and w e re …in t h e re a lm of scie n ce
would overtake us by 2025. fiction for the last several decades
Artificial Intelligence and
Machine Learning

Artificial Intelligence Machine Learning

AI is trained final output machine ML is a subset of AI. It is a technique

which mimic like human brain to achieve AI. Ex: Spam Detection
Ex: Amazon Alexa
 Artificial Intelligence and Machine Learning in Industry 4.0

Breakdowns of industrial development and the great changes in related categories

Industry Industry Industry Industry

1.0 2.0 3.0 4.0

1760-1830 1870-1914 1970-2000 2015 -2050?

Mechanization,
stream and water Mass production Electronic and IT Artificial intelligence
power and Electricity systems, Automation
 Applications of AI
& ML
1. Automated Customer Support
• Online shopping experience has been greatly
enhanced by chatbots because of the following
reasons:

• The y inc re a se use r re te ntio n by se nding

reminders and notifications
• They offer instant answers compared to human
assistants, thus reducing response time
• Chatbots provide upselling opportunities through
personalized approach
2. Personalized Shopping Experience
• Implementation of artif ic ial intelligence makes it
possible for online stores to use the smallest piece
of data about every followed link or hover to
personalize your experience on a deeper level.

• This personalization results into timely alerts,

messages, visuals that should be particularly
interesting to you, and dynamic c ontent that
modifies according to users’ demand and supply.
3. Healthcare
• AI-enabled workf lo w assistants are aiding doctors free
u p t h e i r s c h e du l e s , re du c i n g t i m e a n d c o s t by
streamlining processes and opening up new avenues for
the industry.

• In addition, AI-powered technology helps pathologists in

analyzing tissue samples and thus, in turn, making more
accurate diagnosis.
4. Finance
• Automated advisors powered by AI, are capable of
predicting the best portfolio or stock based on
preferences by scanning the market data.

• Actionable reports based on relevant f inancial data is

also being generated by scanning millions of key data
points, thus saving analysts numerous hours of work.
5. Smart Cars and Drones
• With autonomous vehicles running on the roads and
a uto no mo us dro ne s de liv e ring the shipme nts, a
signif ic ant amount of transportation and service related
issues can be resolved faster and more effectively.
6. Travel and Navigation

• With AI-enabled mapping, it scans road information and utilizes

algorithms to identify the optimal route to take, be it in a bike,
car, bus, train, or on foot.
7. Social media

• Face book uses advanced machine learning to do

eve rything f ro m se rv ing c o nte nt to yo u and to
recognize your face in photos to target users with
advertising.

• Instagram (owned by Facebook) uses AI to identify

visuals.

• LinkedIn uses AI to offer job recommendations,

suggest people you might like to connect with, and
serving you specific posts in your feed.
8. Smart Home Devices

• The connected devices of smart homes provide the

data and the AI learns from that data to perform certain
tasks without human intervention.
9. Creative Arts

• AI-powered technologies can help musicians create

new themes.
10. Security and Surveillance

• AI is making possible for humans to constantly

monitor multiple channels with feeds coming in from
a huge number of cameras at the same time.
Sophia is a first AI humanoid robot developed by Hong Kong-based company Hanson
Robotics

Sophia introduced herself and spoke to the

students appearing for their exams.
YouTube Link : https://www.youtube.com/watch?
v=WATLfjRHySU

India welcomes Robot Sophia for the first-ever interactive session in

Kolkata
 II. Career in AI &
ML
• There is a scope in developing the machines in
game playing, Speech recognition, language
detection machine, computer vision, expert
systems, robotics, and many more

• As per International Data Corporation (IDC)

Worldwide AI Guide, spending on AI systems will
accelerat e over t he next several years as
organizations deploy AI as part of their digital
transformation efforts & to remain competitive
in the digital economy

• Global spending on AI is forecast to double over

the next 4 years, $50.1 billion in 2020 to more
than $110 billion in 2024.
 Avenu
es
Hospital and Medicine Cyber Security

Game Playing Face Recognition

Speech Recognition Transport

Understanding
Marketing & Advertising
Natural Language

Computer Vision
 Avenues

India Abroad
• AI covers many areas like medical diagnosis, stock • Intel offers job for AI and Robotics specialist.
trading, robot control, scientific discovery.
• NASA is the best place to get job in AI in space
• If you have the B.E / M. Tech degree in AI and ML, science.
you have the job opportunities in ISRO.
• US tech companies are prepared to spend over $1
• You also have option to go in various top level billion by 2020 in the process of poaching AI
microchip manufacturer companies like Intel. talent from wherever they can get it.

• Indian institute of Biology offers research in AI and • UK’s demand for AI skills has been growing much
robotics faster than that in the US, Canada and Australia.
• Some AI job includes machine learning engineer,
data scientist, business intelligence developer,
research Scientists, and AI engineer.
 III. AI & ML to drive growth of
Start ups

.
• S t a r t u ps e cosy st e m , h a s be e n • With the rising technologies like
nourishe d w ith the adve nt of AI, IoT and ML, its interesting to
technology, and has given rise to w a tch the cha nging fa ce of
more evolved business processes. Indian SMEs and startups.

• These days Logistics, accounts,

marketing and team performance &
HR have all been supported by AI
technology.
 IV. Skills for success in AI & ML
• Working with AI requires an analytical thought process
and the ability to solve problems with cost effective and
efficient solutions.

• Professionals need technical skills to design, maintain

and repair technology and software programs.

• Those interested in becoming AI professionals need a

education qualif ication based on foundations of maths,
technology, logic and engineering prospective.

• Cognitive Science skills.

V. Conclusions
• As an Artif icial Intelligence aspirant, you have ample of job opportunities in this
field.

• Artif icial intelligence will transform the global economy, and AI jobs are in high
demand.

• According to International Data Corporation (IDC), the number of AI jobs is

expected to globally grow 16 percent this year.

• AI careers are future-proof, meaning they are likely to survive well into the future.

• Getting an education in AI is challenging and requires persistence and personal

initiative.
THANK YOU
Presented by;
RAGANI RANJAN. .
ARTIFICIAL INTELLIGENCE
&
MACHINE LEARNING

Presentation by:
Dr. SANDEEP RANJAN
TABLE OF CONTENTS

• INTELLIGENCE

• ARTIFICIAL INTELLEGENCE

• ARTIFICIAL INTELLEGENCE SUBSETS

• MACHINE LEARNING

• APPLICATIONS OF MACHINE LEARNING

• INTELLIGENCE

• Who is intelligent?

• All living organisms are intelligent.

• They interact with their environment and survive.

• Examples from our own world

➢Crossing a road

➢Discovering alternate paths

➢Writing a poem, drawing a picture, creating a new recipe

• ARTIFICIAL INTELLIGENCE

• Living beings are intelligent; but are man made non living beings also intelligent???

• Can a machine

➢make discoveries?

➢pass a ruling order in a court?

➢compose a symphony?

➢go for a PLAN B?

➢decide to wait or let go?

• ARTIFICIAL INTELLIGENCE

• Traditional computers are powerful but not intelligent

• They can compile MBs and GBs of code but may get stuck at a minor logical
error

• Artificial intelligence is a field of computer science which aims to make

computer systems that can mimic human intelligence.

• Just as we humans act when we don’t have exact information about a

situation but still go ahead and choose one of the many possible moves.
• ARTIFICIAL INTELLIGENCE

• Why make machines INTELLIGENT?

• To reduce our effort and help the society advance

➢share our load

➢make use of massive number crunching power of CPUs

➢perceive things and try to realize them

➢perform in our absence/ without our guidance

• ARTIFICIAL INTELLIGENCE SUBSETS

• MACHINE LEARNING

• ARTIFICIAL NEURAL NETWORKS

• DEEP LEARNING

• COMPUER VISION

• NATURAL LANGUAGE PROCESSING

• SPEECH RECOGNITION
• MACHINE LEARNING

• It is a branch of Artificial Intelligence that gives computers the capability to

learn without being explicitly programmed.

• Focus is on imparting “learning” to machines

• Learning over time and iterations (similar to human experience)

• No longer dependent on rule based programming

• Real world data and observations are fed to the system

• MACHINE LEARNING

• ML algorithms can be broadly categorized into

➢SUPERVISED

➢UNSUPERVISED

➢REINFORCED
• MACHINE LEARNING

• SUPERVISED LEARNING

• Uses ground truth and labeled data

• Requires prior knowledge

• Approximates the relationship between input and output

• Mainly divided into CLASSIFICATION and REGRESSION

• Naïve Bayes, Random Forest, Support Vector Machine, Neural Networks

• MACHINE LEARNING (SUPERVISED)

• CLASSIFICATION

• approximating a mapping function (f) from input variables (X) to discrete

output variables (y)

• Predicting a label

• Spam/ non spam

• Positive/ negative
• MACHINE LEARNING (SUPERVISED)

• REGRESSION

• Approximating a mapping function (f) from input variables (X) to a

continuous output variable (y)

• Predicting a quantity

• Predict salary from age/experience data

• Sales forecast
• MACHINE LEARNING

• UNSUPERVISED LEARNING

• No historical labels

• Learn the inherent structure of data

• Discover the trends in data

• Mainly divided into CLUSTERING and ASSOCIATION

• MACHINE LEARNING (UNSUPERVISED)

• CLUSTERING

• Dividing the population into groups

• Same group members resemble each other compared to other groups

• Connectivity/ centroid/ distribution/density models

• K Means, Hierarchical, KNN, PCA

• MACHINE LEARNING (UNSUPERVISED)

• ASSOCIATION

• Rule based learning model

• Discover rules that describe large portions of your data

• Product placement in malls

• Eg people that buy X also tend to buy Y

• MACHINE LEARNING

• REINFORCEMENT

• Maximize reward in a given situation

• Find the best possible behavior/ path

• Input: initial state of the model

• Output: many possible solutions to a given problem

• Training: reward or punishment

• Iterations: best solution is selected when reward is maximum

• MACHINE LEARNING TOOLS

• PYTHON
• MATLAB
• R
• KNIME
• WEKA
• PYTORCH
• GEPHI
• NODEXL
• NETLOGO…………………………………
• APPLICATIONS OF MACHINE LEARNING

• NATURAL LANGUAGE PROCESSING

• SENTIMENT ANALYSIS

• HANDWRITING RECOGNITION

• SPEECH/ FACIAL RECOGNITION

• CUSTOMER PROFILING (banks and financial institutions)

• RECOMMENDATION SYSTEM (movie and e commerce)

• CUSTOMER CHURN PREDICTION (telecom sector)