Since I have started to write more about Machine Learning, I decided to investigate and clarify what is the big future and wider view of Machine Learning.

What do I mean by Big Picture?

After publishing `Who should learn Machine Learning? and Why?`, I found it’s probably useful for someone new to know what are the benefits of Machine Learning and where is being used. So in this article, I am going to mention a few examples of using machine learning.

1. Virtual Assitance like Google Home/Alexa or Siri

If you look into these new voice assistants, they are getting more and more familiar with our day-to-day life and they are learning to answer better to each one of our questions.

These three will be platforms for using voice and then after they will develop some other tools to work as modules or apps to be added to these things.

Then you can be more and more creative to develop more. As developers, we might develop another app for being used in these platforms.

We might even end up with some other framework to develop one codebase and support it in all these three.

2. Navigations

Google Map and others have probably developed a really comprehensive and accurate solution for navigating to go from one place to another. The more we are using their app they are learning more. They will give us options in the future to develop more and more in their platforms to navigate ways with a better view. or even plan for your driving journey to another city.

This is not even the start. they might add more that you can book your hotel and show it on the map. That’s future and who else worked on this platform better than Google!

3. Video Surveillance

Everyone who has a business or a house has few of these set up for them that they can access it online to check for their security. Police use lots of them to monitor all intersections and even every car’s speeds.

We are getting to have more monitoring systems and what will be important after that is to understand the data, learn from them and notify us for more important events.

4. Social Media

Facebook, Instagram, Snapchat and other ones are already using to some extents machine learning in their product. But the more advanced they get they can show you more relevant data and better posts and pictures.

They can track what you have liked to suggest you the same in your return to the website. Or even notify you with what you probably expect to see.

5. Marketing

There is, of course, the huge money in marketing, so many businesses rely on making advertisements and do marketing for other brands.

Marketing means suggesting the related product the possible customer and who can make this more efficient rather than marketing platform which uses machine learning.

You can already see related products based on your searches on google or social platforms. They can connect them more and guess what you are going to do next and suggest exactly what you need.

6. Customer Support

They are chatbots already out there who learn from older communications between customer and support team to help you get to your answer.

They already know lots of questions are similar and they can answer you with the same response and Machine learning can really make this process quicker.

We will see replacing customer supports in companies with these products really soon.

7. Search Engines

Google is a live example of using machine learning. They are working on making the searches more relevant to you and understand your search query better.

Their crawling robots finds and indexes all data from websites and categorize them better and better. So the quality of the content is getting to be critical.

We will see in the future less useless articles and more of professional opinions.

8. Product Recommendations

Any company who is working on selling something, are working through making better recommendations to its users. Most machine learning experts are working in companies to analyze these data and train a model to come up with a better recommendation.

9. Fraud Detections

Big problem is to detect who is done something suspicious in any platform with lots of transactions. From banks to e-commerce.

Machine learning can learn from old patterns and find new ones. You might argue that’d be possible through normal algorithms, but predicting or finding an old pattern can be done with Machine Learning. This is a really new era and so many are working to start using machine learning.

10. Autonomous Driving

Obviously, this has been more advertised by Tesla and giant companies more than anything else. The more we are tracking normal drives and find what their reactions are in different situations, we can make sure we are more prepared for self-driving cars.

By monitoring through satellites and even cameras and different kind of sensors around the car, we have lots of data to analyze and use machine algorithms to drive the car.

Imagine how much this can be useful for airplanes, trucks, ships and everything else.

11. Translations

Google translate is probably far ahead of the game. More languages are being translated to each other and every day, they are making it better by learning from humans.

This will get to somewhere that everything can fluently translate to another language and then learning a new language might be just a story in history.

12. Speech Recognition

Thinking of speaking and device understand us clearly. We can do it even now and it’s getting better every day.

Machines are learning from old conversations and making progress to understand it. Grammer, meaning, and connections are detectable and maybe machines can understand it better than your audience in the future.

13. Image/Video Processing

It is one of the best and understandable usages of Machine Learning, detecting all objects and understanding the difference between similar objects, tracking an object in the video or just finding something in tons of images.

So many use cases that they all rely on machines to process gigabytes of data.

14. Medical diagnosis

What if we say, machines are intelligent enough to diagnose your sickness. What if we can eliminate humans error and understand the issue better. This is huge and already doctors are spending so much time in their education to learn from others and books to diagnose diseases.

If we can come up with a learning algorithm for machines and make it better every day, we will be able, to sum up, the time spent for all doctors and make a smart doctor who has all the knowledge available and can not make a mistake.

This is a dream, hard to imagine now but so many are using machine learning to find patterns and use them to make better decisions.

15. Teaching to humans

Considering all educations are based on human teachers, and we’ve been discussing robotic ones in the past few years, what if we want to customize it based on each person? can’t we track everyone’s learning and make it better for another person who is interested in the same thing?

This has been a big subject and so many are working to find better ways to educate children. Future machine learning can help a lot to have a bigger effect.

16. Predictions/Forecastination

Predicting events in future or forecasting weather are all based on events and actions of the past, we all love to know to guess what is happening in a day or a month time.

We can guess what’s going to happen to any tool or a city of maybe destiny of a person. Yes, there are some that being used for Stocks and bitcoin. But more and more will be used in other areas.

17. Job Matching / Date Matching

If we know each individual personality, can’t we match them with what they want in their life or job? Job Matching websites are working to make better matching from the person’s interest to companies needs. Something that nowadays recruiters are trying to do but they have lots of personal interests and mistakes.

So one of the usages of machine learning can be helping people find their possible dream jobs.

Machine Learning is big enough, so much data is being stored in databases everywhere and people are not able to read them all. They need analyzing, finding patterns and making decisions to find answers. If you start today even we know machine learning has a long history, you’ll be still ahead of the market and needs of societies.

I will talk more about machine learning and happy to hear if you have got any opinion.