Machine Learning for Everyone: From Hype to Humanization

MACHINE LEARNING FOR EVERYONE: FROM HYPE TO HUMANIZATION

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Danny and Mike are two friends, attending the course on Machine Learning organized by their school. Just after

the

first

class,

they

both

indulge

in

a

long

conversation.

Mike: Hey Dan, what a fantastic session it was! I didn’t know that machines have such great potential with learning.

Danny:

I didn’t get you, Mike? Learning is an explicit

quality, and humans have indeed taught the machines this art of learning on their own, which we commonly known as machine learning.

Mike:

So, you mean that we humans do not need to

imply our knowledge of our day-to-day tasks, because machines can do it for us, right? I thought that the actual

machine

learning

is

just

a

hype

created

in

society!

Danny: and

Ohh, it seems that you still don’t know where

how

machine

learning

has

established

footprints in varied applications industry-wide.

its

Mike:

Uhm, yeah, like I used to think that scientists

feed programs into machines and then machines can work for humans. That’s it.

Danny:

Mikey, my friend, I think you haven’t yet come

across real-time use-cases of machine learning. I must tell you so much.

Mike:

Certainly,

please

do

educate

me

about

the

scope and reach of machine learning.

Danny:

Mike, let me brief you about what is machine

learning? First of all, Machine learning is a subfield of Artificial Intelligence, where ML developers feed data in computer systems and program them to use that data to learn on their own without human intervention.

To explain it better, I am going to educate you about the

varied

applications

of

machine

learning

across

fields such as- healthcare, banking & finance, data analytics,

marketing

&

sales,

eCommerce,

cybersvecurity, commuting, and email communications.

Machine Learning Applications Across Different Industries

Machine Learning in Healthcare Machine

learning

incorporates

several

tools

and

techniques

used

for

prognostic and diagnostic issues of everyday lives in the healthcare domain.

Some of the common use-cases of machine learning in the healthcare sector are,

ML for Detection and Diagnosis of Disease-

Machine vision is at an early adoption for detecting symptoms of the patients so that doctors can address patients’ health beforehand. Also, doctors are attempting medicine recommendations, overall diagnosis, and readmissions for social advantage.

Treatment Recommendation-

Depending on the patient’s previous health record, machine learning can aptly recommend which treatment is going to suit-well to the patient.

Discovery of Drugs-

Healthcare and drug research are a crucial industry impacting the overall development of a nation. Machine learning also helps in providing approaches that improve decision-making while drug-selection with abundant specifiedquestions over a vast data pool.

Machine Learning Approach for Prediction of Pregnancy-

Machine

learning

can

monitor

mother

and

fetus

health,

and

enable

diagnosis of any complications. This life-saving power of ML lowers the risks of miscarriages and pregnancy-related diseases.

Machine Learning in Banking & Finance Most of the banking and finance matters deal with vast amounts of data, and machine learning works well with large volumes of data to detect anomalies and nuances. Some of the implications of machine learning in the banking and finance industry are,

Fraud Detection-

Programmers train machines to catch abnormal finance behaviors, and this way, finance companies, and banks are saving on their operational costs by limiting exposure to fraudulent activities.

Credit Scoring-

Banks use AI intended credit lending applications to find out low-performing loans and credit scores of their customers.

Insurance Underwriting-

AI analyzes a variety of factors in the credit decision-making process like the behavior of traditionally underserved borrowers and avails acute underwriting.

Money laundering prevention-

machines detect suspicious activities, and hence finding fraud is easy to prevent money laundering.

Robo Advisory-

Customers use AI chatbot applications and mobile assistance to reach their financial

targets.

These

AI/ML

managing savings, and more.

apps

assist

them

with

their

spending

rates,

Machine Learning to Boost your Predictive Analytics

Machines Learning works wonders for handling large data sets by giving

predictive

results

in

a

short

time.

It

reduces

the

work

of

computer-coders as machines learn on their own by getting real-time data. Some use-cases of machine learning in data analytics,

Analytics platform-

Employers provide quick analysis tools to their employees so that they can work efficiently with unified data and tools.

Analytics services-

The E2E solution providers satisfy companies’ custom analytics needs and turnkey solutions.

Real-time analytics-

ML is used to explore data, though unstructured so that users can get time-sensitive decisions without any disruptions.

Image recognition and visual analytics-

AI algorithms analyze data piles of images and videos and derive meaningful insights.

Machine Learning For Marketing & Sales

Marketing & Sales is all about getting close to the end-customer, and this can pertain when companies very well know about their customers’ preferences.

Machine

learning

is

the

ideal

choice

when

assisting

companies in their sales and marketing goals. Let us see a few ML applications,

Marketing Analytics-

Artificial

Intelligence

systems

analyze,

learn,

and

measure

the

marketing efforts of the PR team. These systems give out expert insights that drive engagement, traffic, and revenue.

Personalized Marketing-

Internet

users

webpages,

get

which

ads is

of

one

visited of

the

online

products

techniques

companies for customer-specific marketing.

used

even by

on

other

eCommerce

Context aware marketing-

Marketing

executives

use

Machine

Vision

and

Natural

Language

Processing for creating context-aware ads for specific users based on their interests.

Sales forecasting for pre-sales-

Based on previous sales outcomes and customer contacts, brands use AI automated forecasts for attaining sales accuracy.

Sales content personalization-

AI analyses the needs of high-priority leads by watching their browsing patterns and matches the right content to meet their requirements.

Machine Learning in E-Commerce The most vital and trending industry today is the eCommerce industry.

Machine Learning is empowering many online businesses in many ways like,

Recommender systems-

One

of

the

most

potent

marketing

styles

currently

is

on-site

recommendations. ML reveals customized user recommendations that benefit eCommerce companies, and they have noticed a 30% hike in sales because of such ML advice.

Content Personalization-

The AI bots study user patterns, interests, and browsing methods and decide the type of content to display for each user. Such personal-touch boosts sales amongst the customers.

Chatbots-

AI has taken personalization to a very high-level. Customers feel personal

preference

and

respond

much

better

with

the

businesses,

which ultimately benefits the online companies.

Dynamic Pricing-

Studying customers’ browsing history, shopping patterns, times, and more, ML automates customized sales and discounts for users. Such an active style of pricing works out favorably for e-businesses.

Machine Learning for Cybersecurity Artificial Intelligence is used to provide security and authentication in sophisticated systems. Some of them are,

Password protection & Authentication-

Machine

learning

adapts

user

profiles

by

checking

their

keystroke

styles, typing speeds, and else to provide multi-factor authentication. It suggests stronger passwords whenever necessary.

Cyber threat detection-

AI detects anomalies early and help the brands discover vulnerabilities beforehand.

AI

finds

out

even

the

minutest

changes

in

human

interaction patterns to identify red-flags in the process.

Phishing Detection and prevention control-

AI

combats

the

phishing

attacks

very

well

by

analyzing

internal

communication systems and detecting any unusual event.

Vulnerability management-

Machine learning can track hackers’ activities and analyze their attack patterns. Then, companies can use these ML reports to enlighten their employees about such attacks so that they stay protected.

Predicting Travel Mode of Individuals by ML AI and ML have been the most useful in reducing the tiring commute time of workers. Some of the ways how AI is helping to tackle the complexity of transportation,

Predictions-

Google maps help in sharing users’ locations, which, in turn, helps to detect the traffic and speed of its movement. This way, ML can suggest

the

commuters

to

find

the

fastest

routes

to

get

to

their

destinations.

Ridesharing apps-

ML helps the ride-sharing apps to find out the price of user rides, waiting times, and detour rides availability. Apps like Lfyt and Uber are a boon today.

Auto-pilot-

the earliest use of AI is in airplanes. The cockpit requires minimal human pilot effort. Rest, since 1914, planes have been using AI autopilot mode for flying.

Machine Learning to Improve the Email Experience Email is an essential part of one’s life, and you cannot guess how magically AI and ML are making your work routine easy. Let’s see,

Spam filters-

AI uses simple filters to keep unwanted emails, marketing emails, and promotional ones from unknown ids away from your inbox, i.e., in your spam mails.

Smart Email Categorization-

Gmail uses an efficient AI technique to keep your emails categorized into

primary,

promotional,

and

social

mails

in

groups.

Gmail

is

continually learning as every time you mark an email important, it remembers.

Danny (continuing): So, Mike, I hope these realtime examples of Machine learning have brought insights to you.

Mike:

I am excited, Danny! These examples of

machine learning and implementations of Artificial Intelligence have sparked me up. Now I know that all the hype I heard about ML is nothing but a proven reality. Thank you so much, my friend, Thank you!

Wrapping Up

Many of you might have cleared the perceptions of new and upcoming ML and AI after reading this post. Now that you know the true potential of machine learning; get the best AI and ML development services from Bacancy to yield high-performing AI/ML apps.

Thank You