ML 1.6 Applications of Machine Learning
v Applications of Machine Learning: -
1.
Image Recognition
2.
Speech Recognition
3.
Traffic prediction
4.
Product recommendations
5.
Self-driving cars
6.
Email Spam and Malware Filtering
7.
Virtual Personal Assistant
8.
Online Fraud Detection
9.
Stock Market trading
10.
Medical Diagnosis
11.
Automatic Language Translation
1) Image Recognition: -
Ø Image recognition is one of the most
common applications of machine learning. It is used to identify objects,
persons, places, digital images, etc. The popular use case of image recognition
and face detection is, Automatic friend tagging suggestion.
Ø Facebook provides us a feature of auto
friend tagging suggestion. Whenever we upload a photo with our Facebook
friends, then we automatically get a tagging suggestion with name, and the
technology behind this is machine learning's face detection and recognition
algorithm.
Ø It is based on the Facebook project named
"Deep Face," which is responsible for face recognition and
person identification in the picture.
2) Speech Recognition: -
Ø While using Google, we get an option of
"Search by voice," it comes under speech recognition, and it's
a popular application of machine learning.
Ø Speech recognition is a process of
converting voice instructions into text, and it is also known as "Speech
to text", or "Computer speech recognition." At
present, machine learning algorithms are widely used by various applications of
speech recognition. Google assistant, Siri, Cortana,
and Alexa are using speech recognition technology to follow
the voice instructions.
3) Traffic prediction: -
Ø If we want to visit a new place, we take
help of Google Maps, which shows us the correct path with the shortest route
and predicts the traffic conditions.
Ø It predicts the traffic conditions such as
whether traffic is cleared, slow-moving, or heavily congested with the help of
two ways:
·
Real Time location of the vehicle form Google Map app and sensors
·
Average time has taken on past days at the same time.
Ø Everyone who is using Google Map is
helping this app to make it better. It takes information from the user and
sends back to its database to improve the performance.
4) Product recommendations: -
Ø Machine learning is widely used by various
E-Commerce and Entertainment companies such as Amazon, Netflix,
etc., for product recommendation to the user. Whenever we search for some product
on Amazon, then we started getting an advertisement for the same product while
internet surfing on the same browser and this is because of machine learning.
Ø Google understands the user interest using
various machine learning algorithms and suggests the product as per customer
interest.
5) Self-driving cars: -
Ø One of the most exciting applications of
machine learning is self-driving cars.
Ø Machine learning plays a significant role
in self-driving cars.
Ø Tesla, the most popular car manufacturing
company is working on self-driving car. It is using unsupervised learning
method to train the car models to detect people and objects while driving.
6) Email Spam and Malware Filtering: -
Ø Whenever we receive a new email, it is
filtered automatically as important, normal, and spam.
Ø We always receive an important mail in our
inbox with the important symbol and spam emails in our spam box, and the
technology behind this is Machine learning.
Ø Below are some spam filters used by Gmail:
·
Content Filter
·
Header filter
·
General blacklists filter
·
Rules-based filters
·
Permission filters
Ø Some machine learning algorithms such
as Multi-Layer Perceptron, Decision tree, and Naïve
Bayes classifier are used for email spam filtering and malware
detection.
7) Virtual Personal Assistant: -
Ø We have various virtual personal
assistants such as Google assistant, Alexa, Cortana, Siri.
they help us in finding the information using our voice instruction. These
assistants can help us in various ways just by our voice instructions such as
Play music, call someone, open an email, Scheduling an appointment, etc.
Ø These virtual assistants use machine
learning algorithms to record our voice instructions, send it over the server
on a cloud, and decode it using ML algorithms and act accordingly.
8) Online Fraud Detection: -
Ø Machine learning is making our online
transaction safe and secure by detecting fraud transaction. Whenever we perform
some online transaction, there may be various ways that a fraudulent
transaction can take place such as fake accounts, fake ids,
and steal money in the middle of a transaction. So, to detect
this, Feed Forward Neural network helps us by checking whether
it is a genuine transaction or a fraud transaction.
Ø For each genuine transaction, the output
is converted into some hash values, and these values become the input for the
next round. For each genuine transaction, there is a specific pattern which
gets change for the fraud transaction hence, it detects it and makes our online
transactions more secure.
9) Stock Market trading: -
Ø Machine learning is widely used in stock
market trading.
Ø In the stock market, there is always a
risk of up and downs in shares, so for this machine learning's long
short term memory neural network is used for the prediction of stock
market trends.
10)
Medical Diagnosis: -
Ø In medical science, machine learning is
used for diseases diagnoses. With this, medical technology is growing very fast
and able to build 3D models that can predict the exact position of lesions in
the brain.
Ø It helps in finding brain tumours and
other brain-related diseases easily.
11)
Automatic Language Translation: -
Ø Nowadays, if we visit a new place and we
are not aware of the language then it is not a problem at all, as for this also
machine learning helps us by converting the text into our known languages.
Ø Google's GNMT (Google Neural Machine
Translation) provide this feature, which is a Neural Machine Learning that
translates the text into our familiar language, and it called as automatic
translation.
Ø The technology behind the automatic
translation is a sequence-to-sequence learning algorithm, which is used with
image recognition and translates the text from one language to another
language.