About Machine Learning

Machine learning is an application of artificial intelligence (AI) that provides systems the ability to automatically learn and improve from experience without being explicitly programmed. It is a sub-area within the Artificial Intelligence domain. Machine learning focuses on the development of computer programs that can access data and use it learn for themselves. Thus when it encounters data it evaluates it to see if it fits a pattern and then takes action as prescribed by the pattern. If it does not fit a pattern then it takes predefined actions.

The concept of Machine Learning has been around for over half-a-century now. However, with the astronomical growth in data, the full potential of Machine Learning is being investigated. It is being realized that it can analyze huge amount of data and take predictive action based on the previous learning. Thus the core aspect here is ‘pattern recognition’ which helps it to take the correct action. Realizing the huge potential of Machine Learning, big companies are harnessing it to understand consumer behavior and to provide suggestions to him or her which will help in decision making. Thus companies like Facebook, Amazon or Alibaba are using it to understand what the surfer is looking for and provide related suggestions which will help them to make the buy decision. Many websites offer a ‘things you may like’ feature which uses Machine Learning to predict consumer likes. Similarly, friend suggestions on Facebook and Mobile phone suggestion on different websites like Amazon or Flipkart. As machines are learning and understanding user behavior hence the term ‘Machine Learning. Types of Machine Learning The next question that comes up is,

How do Machines Learn?

There are different ways in which Machines learn. The primary ways are Supervised Learning, Unsupervised Learning, Semi-Supervised Learning and Reinforced Learning.

We call it Supervised Learning when the input and the outputs are known. Thus any discrepancy in the desired outcome is flagged as an error. This is popular when the inputs and the outcomes are predictable and known.

Unsupervised learning happens when the data is unknown and the machine will have to read data and take action based on the data. Examples are ‘finding nearby hotels near a address on a map’ or ‘finding a Chinese Restaurant near my home’.

A mix of both Supervised and Unsupervised Learning is Semi-Supervised learning. Examples are voice recognition or face recognition.

Incase of Reinforced Learning, the algorithm will work out different paths to achieve the result and then decide on the best path to maximize the award. In recent times, the term Machine Language has become very popular. Everybody seems to be talking about it and there is talk of great demand for it. Everyone is predicting the demand for machine learning and data science experts and foresee an exponential growth. No doubt that Machine learning is one of the fastest growing fields in the technical world. All major technology companies are investing heavily in machine learning and data science to improve their products.

So, what programming languages should one learn to land a machine learning or data science job?

Programming Languages that work on Machine Learning

It is commonly thought that Machine Learning works with Python or R-Programming. However it is largely unknown that there are a number of programming languages that are popular in this area. Even traditional languages like Java, C++, Javascript can be used in Machine Learning. We also see that in the past couple of years, there’s a sharp increase in the popularity of these languages in machine learning and in the context of data science.

Top 8 Programming Languages For Machine Learning & Data Science:

1. Python

2. Java

3. R

4. C++

5. C

6. JavaScript

7. Scala

8. Julia

As expected, Python is a clear leader. It’s followed by Java, R, and C++. It is also observed that Python’s lead over Java is increasing in the period of past one year. Catching up fast is R-Programming which is currently at 3rd position. Considering the growing acceptance of Machine Learning amongst companies, experts predict tremendous growth in opportunities in this domain.

For those evaluating career options, it is recommended to add this skillset to their kitty and move in at the earliest opportunity. For more questions, call us and discuss about the learning opportunities here –

This article is written by Abhijoy Mitra. The views shared are those of the individual and he has no connection to any coaching centers or teaching faculties. Palium conducts classroom and online trainings based on demand to meet specific needs of customer. In course of training participants learn and understand concepts from knowledgeable trainers which help them to implement them at their workplace.

To learn Machine Learning and fast-track your career, consider the following courses Offered by Palium relating to Machine Learning are -

1. Machine Language using Python

2. Machine Language using R-Programming