Why is Machine Learning The Future?

Machine Learning is a field of study of smart and efficient use of data and existing algorithms to make machines imitate humans in performing tasks with greater accuracy. It is one of the fastest growing branches in Computer Science , along with Artificial Intelligence. Machine Learning can be rightly called as a subset of artificial intelligence, as a lot of ML algorithms and results are of AI .

Automation of Routine Tasks

We are living in a fast moving world where people have no time to carry out their regular chores manually. Nearly half of the population is migrating towards automation with the advent of inventions like Alexa, Siri, Google Assistant to name a few. This allows people to explore their other interests and come up with creative solutions to complex problems.

Predictive Analysis

Machine Learning techniques are widely used in making predictions of events that are likely to occur in the future and involve humongous data. Examples of this can be predicting which team will win the cricket or football match or who will win the presidential elections or what will be tomorrow’s weather in a particular area etc. All these results are predicted with accuracy and precision after taking optimized decisions from the model built using ML algorithms.

Innovation in Services

How does Google know about your Amazon and Flipkart search history? How does Youtube recommend your favourite shows and music videos? On one hand we really enjoy using these things as it makes our lives comfortable but on the other it makes us wonder who is the one behind all this. The field of ML is so broad that one can focus on diverse aspects of it at one time. The diversity and feasibility of the algorithms has made it possible to develop and build stuff which were previously considered impossible to construct. This creates a lot of employment opportunities for people in various domains.

Popular Algorithms in the Field of ML

Top 4 Machine Learning Algorithms that helped us during this dynamic season of technology.

• Supervised

• Unsupervised Learning

• Semi-supervised Learning

• Reinforcement Learning

In supervised learning , the input dataset is provided to the model and it finds a suitable mapping function y=f(x) where x is the input.

In unsupervised learning approach, we infer patterns from the input data with a suitable algorithm which the model decides by itself. Clustering problems are a part of unsupervised learning.

The semi-supervised learning approach is a combination of the two approaches we have seen so far. It involves both labeled and unlabeled data .

Reinforcement learning is a feedback based learning approach wherein the results of the first trial is given as input to our next trial. It can also be called an intelligent system which learns to act according to the environment by seeing its own responses.

Career Opportunities in ML

If one is interested in statistical analysis , automation and developing new technologies that can solve real-world problems , then nothing can stop them from becoming a Machine Learning engineer. Let us take a look the the educational qualifications that companies look for −

He/She must be a graduate in Engineering with a domain as Computer Science or Information Technology.

He/She must have taken up a Bachelors in Science course with Artificial Intelligence or Statistical mathematics or Computer science as domain.

Even if one didn't take up a bachelor’s course in any of the above , you can still work as an ML intern after doing short term courses in Machine Learning that are available in several online platforms.

Make sure to be good at the following stuff before applying for any position

• Programming languages like Python(most important) , C++ and C#.

• Regression learning

• Calculus and algebra

• Statistics

Scope of ML Worldwide

Machine Learning has become a highly demanded skill among recruiters especially in the west. The USA offers nearly $100000 for an ML engineer on an average. They are trying to integrate ML with interdisciplinary fields like Robotics and Quantum computing. This proves that ML is definitely a lucrative career with a promising future.

Conclusion

Machine learning, being one of the fields of AI, has advancements coming up every now and then. Hence, as an ML engineer one must keep updating themselves in order to keep track of the latest trends . It takes a lot of effort , dedication and passion to master this field just like any other field. But with consistency and practice it is definitely possible and highly rewarding with monetary benefits. The pay scale of ML scientists is nothing lesser than a professional working in any other field like healthcare or finance. The future lies in the hands of youngsters who will be ruling the world through ML and AI.