Machine
learning:
Machine Learning is
undeniably one of the most influential and powerful technologies in today’s
world. More importantly, we are far from seeing its full potential. There’s no
doubt, it will continue to be making headlines for the foreseeable future. This article is designed as an introduction to the Machine Learning concepts,
covering all the fundamental ideas without being a too high level.
The
term Machine Learning was coined by Arthur Samuel in 1959, an American pioneer
in the field of computer gaming and artificial intelligence and stated that “it
gives computers the ability to learn without being explicitly programmed”.
In machine learning, the
underlying algorithm is selected or designed by a human. However, the
algorithms learn from data, rather than direct human intervention, about the
parameters that will shape a mathematical model for making predictions. Humans
don’t know or set those parameters — the machine does. Put another way, a data
set is used to train a mathematical model so
that when it sees similar data in the future, it knows what to do with it.
Models typically take data as an input and then output a prediction of
something of interest.
Machine Learning is used anywhere from automating mundane tasks to
offering intelligent insights, industries in every sector try to benefit from
it. You may already be using a device that utilizes it. For example, a wearable
fitness tracker like Fitbit, or an intelligent home assistant like Google Home.
But there are much more examples of ML
in use.
Prediction
— Machine learning can also be used in prediction systems. Considering the
loan example, to compute the probability of a fault, the system will need to
classify the available data in groups.
Image recognition
— Machine learning can be used for face detection in an image as well. There is
a separate category for each person in a database of several people.
Speech Recognition
— It is the translation of spoken words into the text. It is used in voice
searches and more. Voice user interfaces include voice dialing, call routing,
and appliance control. It can also be used a simple data entry and the
preparation of structured documents.
Medical diagnoses
— ML is trained to recognize cancerous tissues.
The financial industry and trading
— companies use ML in fraud investigations and credit checks.
Types
of Machine Learning?
Machine
learning can be classified into 3 types of algorithms.
1. Supervised
Learning
2. Unsupervised
Learning
3. Reinforcement
Learning
0 Comments