1. Machine Learning in Finance Industry
Whenever the context of the financial market is presented for building a finance mobile app, the major concerns are security, investment accounting, keeping track of revenues, and generating reports based on the data collected.
These mobile apps have a crucial role to play as monetary transactions are involved whether it is a consumer mobile application or an enterprise app built specifically for banks or such other financial institutions.
If these apps are armed with Machine Learning it will generate results that were only imagined a decade ago. For instance, what we call ‘smart bank’ can sift through your transactions, discern the relevant info and make suggestions according to your financial behavior in past.
Automated investment bot is another example on the same lines. It conducts technical analysis of the stock, currency or commodity markets and make investments on the basis of the defined algorithm and make suggestions for potential investment opportunities that will help you build your portfolio.
2. Machine Learning For E-Commerce Apps
Machine Learning E-commerce apps are creating waves in the world of technology as well as mankind. Amazon is already forward in leveraging Machine Learning to suggest similar products to its customers.
If you will keep on clicking different pages, it will learn you are not interested to buy from the current suggestions, it will start making a different suggestion. It learns not only from you but from the combined experience of people who bought similar products and several other social products that you may have never even thought of. This gives the customers more personalized experience and improves the user engagement which in turn kicks the revenue graph quarter to quarter.
3. Machine Learning For Healthcare Industry
Machine learning has the capabilities that you could leverage to merge technology with medical science. It learns the same way as a doctor does and is completely error-free.
Machine learning covers diagnosis, prescription, treatment, and even the most complex medical procedures. Computers with machine learning enabled in them are now able to compare symptoms with the fed database. They can dig into the genetic details and suggest and perform millions of possible diagnoses along with providing a proper cause and effect report like a human doctor.
With the latest biometric sensors and relevant database, machines can actually analyze, process, and compare data and provide faster and effective diagnoses for several medical conditions.
4. Machine Learning in Transportation Industry
Gartner envisages 250 million+ smart cars hitting the road by 2020 which are connected to high-tech networks and with each other. So, are you ready to tie seat belts in your self-driving car?
The proof that this prediction will come true is companies like Google, Uber, Tesla are dedicatedly pushing the self-driving car projects with major investments and the progress they made is uncanny.
Autopilot concept has evolved beyond normal functions of maintaining the speed, slowing down as and when necessary, staying in the lane to changing the lane on its own, making the transition from one highway to another, self-park, and respond when summoned.
The possibility of human error can actually be eliminated as there is zero human involvement. How it will affect the lives of over-exhausted drivers or will it make the road any safer, all these theories are yet to unfold.
5. Machine Learning in Fitness Industry
The health and fitness industry is flooded with mobile apps which can analyze your daily activities like your steps, rhythm of jogging, exercise timing variations and a lot more. Tracking is one thing and aiding in the one’s life is another thing. In near future, these apps will analyze an enormous amount of anonymous user data and will provide trending information along with personalized suggestions on how you can alter your diet or activities to achieve your health goals faster.
Machine Learning is no longer in future, it is here already. It is already deployed in its rudimentary version in many industries but there is a lot to work upon. Today is not the time to count on Machine Learning completely but the coming era belongs to Machine Learning. Take your first step towards future today and learn more about Machine Learning and how it can bring value to your life and business.