What is the scope of machine learning in the future?

Data Science, AI and ML
#1
The scope of machine learning is progressive primarily fuelled by the increasing complexity of business environment in today’s world. The concept of automation and designing supervised systems which can take decisions from itself without explicit coding of business logic is fuelling the growth of machine learning in businesses all over the globe.

In addition to this, the growth of data science and leveraging statistics in business decisions is also responsible in taking machine learning to the next step.
#2

As we have seen machine learning techniques are used in medical fields, transportation, industries etc. machine learning techniques are now used to suggest antibiotics for specific disease.

In future, AI with machine learning may be more advanced in automatic vehicles and can take complex decisions like humans. In medical sector, the ML with AI systems can diagnose patients and prescribe treatment for their specific conditions. ML is developing in many areas of the life, it is only going to integrate deeper as the AI technology grows.

#3

Is the era of machine learning coming to an end?

Not at all.

What we’re seeing right now is only the beginning.

Here are some machine learning trends I believe we will see in the future:

Our knowledge of neural networks will vastly improve.

The most astounding learning algorithms we have at our disposal right now are neural networks.

It will start to make sense to use Natural Language Processing.

ML-based NLP is now in such a bad condition that it can only compete with rule-based engines. That may be an exaggeration, but I believe this ML subfield is still in its infancy.

The primary issue is that different circumstances provide different interpretations of words. Algorithms that identify those circumstances and comprehend linguistic notions on a deeper level have yet to be implemented appropriately, but there’s no reason they can’t be.