We know humans learn from past experiences and machines follow
instructions given by humans, but what if humans can train the machines to
learn from the past data and do what humans can do act much faster, that’s
called Machine Learning.
For example, 1 method
is classification method. It can put data into various groups. The same
classification method used to concede handwritten numbers and also be used to
classify emails into spam and not-spam. It is the same method but it’s fed
different training data and hence it comes up with different classification
Classification | Insideaiml
There are three types of Machine Learning Algorithms:
Here we have a teacher
who gives us instructions i.e training data, which means here in supervised
learning we have inputs also and outputs also and through that given data also
known as labeled data we prepare a model and there we put our new I puts and check
whether we are getting desired output or no and if we get the same output as
per training data, the data given was very accurate and refined and the
algorithm is properly learned and classified, and the algorithm used here is
Naire Bayes Algorithm.
is something where we only have some inputs, and from the available and known
inputs we make clusters or groups according to
similar inputs. Here
we do not have outputs, so we have to generate it by using K-Mean Algorithm.
Maximum learning is done through unsupervised learning.
Now here, this
learning is based on reward and policy. For eg. We have an agent who performs
some action in environment and in return the agent gets some reward/penalty
based on the action performed maybe positive or negative. So according to the
change in environment, the agent makes the policy and based on the policy he
performs his actions in a different manner. So here from the rewards and
penalties, learning is done.
Some of the excited
examples of Machine Learning are:
1. Virtual Personal Assistants
Virtual Personal Assistants | Insideaiml
Siri, Alexa, Google Now are some of the well-known examples of virtual personal assistants. As the name suggests, they
assist in finding specific information, when asked over voice. All you need to
do is activate them and ask “What is my schedule” or maybe “Read the messages”
or maybe set any alarm and accordingly u get answered.
Virtual Assistants are integrated to a variety of
platforms. For example:
Predictions: We use our GPS locations randomly while travelling, so that
detects our current location as well as the location where we want to reach and
guide us accordingly. Also we are guided of the traffic ahead and various
routes we can go through.
Transportation Networks: While we book an ola or cab, the price is estimated
automatically. In this entire cycle, Machine Learning plays a very important
3. Videos Surveillance
Videos Surveillance | Insideaiml
When a alone person is appointed to monitor various
video cameras, that becomes very difficult. So, nowadays the system of video
surveillance is powered by artificial intelligence so the crime is detected
before they are ocuured, hence gives us the alert.
Product Recommendations | Insideaiml
you shop some product online, and after some days you receive emails of the
similar shopping suggestions. You also get some notifications through the same the website from where you have shopped the product earlier, they suggest products
according to your taste and preference.
5. Online Fraud Detection
Online Fraud Detection | Insideaiml
Machine learning is proving its potential to make
cyberspace a secure place and tracking monetary frauds online is one of its
examples. For example, Paypal is using ML for protection against money
I hope you enjoyed reading this article and finally, you came
to know about Machine Learning, Types of machine learning and Real-life applications of machine learning.
For more such blogs/courses on data science, machine
learning, artificial intelligence and emerging new technologies do visit us at InsideAIML.