MACHINE LEARNING – Future ahead

By Ms. SAKSHI RAWAT

PGDM Batch 2020, JIMS Kalkaji

As we all know that COVID-19 is now dominating the world, it is crucial for us to note that in the world of machine learning, many organizations are running their business as they use to operate it earlier. It is obvious that everyone has taken measures to fight the spread of COVID-19. However, many researchers are working hard to keep their progress and innovations in the world of Artificial Intelligence.

The term Machine learning was given by Arthur Samuel in 1959, an American pioneer in the field of computer gaming and artificial intelligence. Machine learning is an application of Artificial Intelligence. It involves the learning of computers from the data that is being provided to them to carry out the tasks. It focuses on making predictions using computer data.

Machine learning provides the systems the ability to improve by themselves without being programmed by the humans. It focuses on the development of computer programs that can access date and use it to learn by themselves. The main goal of machine learning is to allow the computers learn automatically without human intervention.

 In machine learning data is splited into three segments i.e.

Training data: This data is used to make decisions without being programmed.

Validation data: This model is used to do evaluation of model/computer. This data plays a significant role while model is training.

Testing data: After the training of the model is complete, testing data will provide the evaluation of the model.

There are many machinelearning algorithms but most commonly used are:

• Supervised machine learning algorithms: These algorithms produce functions to make the predictions.
• Unsupervised machine learning algorithms: These algorithms are used to train an unlabeled data(data comes with no tag).
• Semi-Supervised machine learning algorithms: These algorithms lie between supervised and unsupervised machine learning algorithms.
• Reinforcement machine learning algorithms: These are used to determine the behavior of the machines to maximize the output.

Applications of Machine Learning

Nowadays, Machine learning is required in many fields or we can say that there are many applications of machine learning. Some of these applications are:

• Surveillance of videos: In today’s time, the video surveillance system uses Artificial Intelligence to detect the crime. They track down the unusual behaviour of human beings and help them in preventing from any kind of mishaps.
• Social Media: Social Media uses machine learning to a great extent like face recognition in Facebook.

• Email spam: Multi-Layer Perception, C 4.5 Decision Tree Induction are some of the spam filtering techniques that are powered by machine learning.
• Machine learning is also used in the detection of malwares.
• Online customer support using Chatbots are now using machine learning for satisfying the needs of the customers.
• Google utilizes machine learning to structure its results and for YouTube’s recommendation system, among many other applications.
• 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 laundering.

The applications of machine learning are not just limited to the above-mentioned points. The use of machine learning can is now expanding day by day.

Languages used in machine learning

It is very difficult to mention a particular language for machine learning. Various researchers have said that the type of language used in machine learning depends on the type of work to be worked upon. But the most common languages used in machine learning are mentioned below:

JAVA: It is the second most preferred language in machine learning. As per the surveys, nearly 15% of data scientists use this language for security purposes like network security where python is least preferrable. JAVA is considered as secured language due to the use of bytecode and sandboxes.

R: R is a graphic-based language used in statistical analyses, computing in machine learning. It is used to explore statistical data through graphs. It is used by data scientist in many big companies like Google, Facebook etc.

JAVASCRIPT: JavaScript is generally opted for machine learning as it helps in visualizing results of machine learning algorithms on a web-based dashboard.It is a high-level, object-oriented, language that is standardized in ECMAScript language specification.

So, we can say that in today’s world, machine learning is present everywhere.