What is Machine Learning?
Machine Learning (ML) is a scientific study that allows computers to learn without any external (human)
interference. It is an application of artificial intelligence (AI) that provides a computer system the
ability to learn patterns and inference automatically. Machine Learning improves the observation of the
computer system and focuses on the development of computer programs to access data and use it to learn by
themselves without any human/user supervising its action or telling it what to do. ML is one of the most
exciting technologies in existence today as it allows a computer to act like humans by possessing the
However, there is a difference between Machine Learning and Artificial Intelligence. AI is a branch of
computer science that emphasizes the creation of intelligent machines that behave and react like humans.
Whereas, ML is an ability that enables a computer to learn by itself and use it as acquired knowledge or
Algorithms of Machine Learning:
The varied machine learning algorithms differ in the type of
data we input and output, the approach of the process and the
type of challenge that is intended for solving. The algorithms
are generically diversified as supervised and or unsupervised
Supervised and semi-supervised learning
Supervised ML algorithms a mathematical model of training
data that consists of one or more inputs and the desired
output. As in the case of semi-supervised learning, the
algorithms learn functions that are used to predict the
desired output for the inputs provided.
In unsupervised machine learning, the algorithms use a set
of data that contains inputs only to find a structure in the
data and learn from the unclassified test data to identify
commonalities and react based on the absence and presence of
the commonalities of new data.
Reinforcement learning concerns with software agents and how
they take actions in a scenario to increase optimization by
discovering errors and rewards and reacting to it.
Most important ways of how ML can help your business are as
Customer Value Prediction
With the use of Machine Learning, businesses can effectively use
customer data and derive meaningful solutions and business
insights. For, ML and Data Mining processes help in predicting
customer behavior and identifies their taste and preferences by
analyzing the purchase pattern. Hence, assembling the retrieved
data and then using it to send individual customers with the
best possible offers based purely on their history of browsing
and purchasing history.
Machine Learning can be used for image recognition that has
the potential to produce numeric and symbolic information
from the images and high-dimensional images that are
provided. The method involves Machine Learning, Data Mining,
Pattern Recognition and discovery of data. Prediction
Management With the correct use of ML, businesses can
discover meaningful insights and patterns hidden in the data
factory and reduce the risks that are associated with
unexpected failures and needless expenses.
Eradicate Manual Data Entry Process
Since Machine Learning primarily functions with the use of pre-existing and new input of data, it
helps in reducing duplication and inaccurate entry of data. With ML’s predictive model algorithms, it
has proven to avoid errors caused by manual data entry which in turn allows employees to invest the
time productively on other business operations.
Machine Learning has surpassed expectations from the previous process of detecting spam where a
rule-based technique was followed. Now, with ML, spam filters are developing new rules with the use of
neural networks to detect spam.
Unsupervised ML is used for developing a product-based recommendation for eCommerce websites using
algorithms to track customers history of purchase and search options and providing them with relevant
Machine Learning uses accurate volumes of quantitative data for efficient financial analysis. It is
used for Portfolio Management, Algorithm Trading, Fraud Detection, and Loan Underwriting. Soon, ML
will include various other features like Customer Service, Sentiment Analysis, Chatbots, and more.
Machine Learning has also proved to be highly effective in the medical scenario, with the use of
superior diagnostics tools and effective medical treatment plans. Hence, improving patients health and
reducing the cost with an accurate diagnosis, readmission prediction, identification of high-risk
patients and medicinal recommendations by using the patient record data along with relevant health
Enhance Customer Satisfaction
Machine Learning helps in improving the loyalty of customers and offers superior customer experience.
The goal is achieved by a thorough analysis of customer behavior in the past, customer requirement and
feedback, all of which are assembled and examined in order to produce effective customer service. The
use of ML in this sector helps in reducing cost and the time in managing the customer relationship.
Cyber Security Improvement
Cyber Security is a major problem faced by business enterprises that can be solved by Machine
Learning. For, ML allows swift detection of a breach and builds better technologies to track and
account for unknown threats.
Over the years, ML has grown prominent in the business sector with its advanced Artificial Intelligence
(AI) applications. It has helped business enterprises and various other sectors with cost reduction
solutions and effective end results. With time, its application will increase in quality and quantity
whilst intensifying the growing popularity of AI.
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