Application of Machine Learning – Introduction
Machine learning is one fashionable innovation that has helped man enhance not solely several industrial and skilled processes however additionally advances everyday living. There is many application of machine learning we can see in our personal and professional life. Companies across the globe are operating on machine learning to yield better business outcomes and drive the innovative campaign of the organization. With its unpredicted horizons, the technology is influencing the common lives of people too. With the emergence of innovative ML applications, a huge quantity of tech enthusiast, talents and resources are venturing into the capacity. These human resources combined with ML innovation can rightfully process the bulk of data, derive meaningful insights and make precise predictions without much of mortal interference.
Machine learning can help us live happier, healthier, and more productive lives. If we know how to harness its power. One day, computers won’t solely replace labor, however additionally mental labor. But how exactly will this happen? And is it already happening?
Here is the list of 10 machine learning application examples
1.Machine Learning Application in Intelligent Gaming
Some of you may remember 1997 when IBM’s Deep Blue defeated Gary Kasparov in chess. But if you weren’t old enough then, you might remember when another computer program, Google DeepMind’s AlphaGo, defeated Lee Sedol, the Go world champion, in 2016.
Go is an ancient Chinese game, much more difficult for computers to master than chess. But AlphaGo was specifically trained to play Go, not by simply analyzing the moves of the very best players, but by learning how to play the game better from practicing against itself millions of times.
2.Application of Machine Learning in Autonomous Vehicles
Autonomous vehicles are one of the best application of machine learning. The future of transportation will never be the same as it is now, once autonomous vehicles will hit the market. Certain Predictions imply that the adoption of self-driving cars will reduce traffic-related issues by nearly 90%.
Though the production of such vehicles is not consumer-centric yet its influence over our future lives is inevitable. Moreover, the total time required for complete adoption of this innovation depends on the regulatory rules which lie beyond the boundaries of technology. Software engineers are heavily dependent on the ML algorithms to design its autonomous feature to enable it to operate on its own.
Application of machine learning to environmental protection. Machines will store and access additional knowledge than any one person could—including impressive statistics. Using massive knowledge, AI might sooner or later establish trends and use that data to make h solutions to antecedently unreasonable issues.
For example, IBM’s Green Horizon Project analyzes environmental data from thousands of sensors and sources to produce accurate, evolving weather and pollution forecasts. It permits town planners to run “what-if” eventualities and model ways to mitigate environmental impact.
And that’s just beginning. Exciting environment-oriented innovations are entering the market every day, from self-adjusting smart thermostats to distributed energy grids.
As per studies, cybercrime damage costs are expected to increase by $6 trillion annually by 2021. Different experts foresaw that companies will invest more than $1 trillion in cybersecurity advancement to cope up with the alarming risk.
Consequently, researchers are developing smart methods to apply machine learning innovation to identify fraud and prevent phishing and cyber-attacks. The defensive mechanism is being trained, using old data records in order to increase the pace of spotting and protecting malicious activities. These ML models have been made accessible to developers already which makes it more interesting to watch how it will gain mass endorsement from customers as well as from organizations.
For many seniors, everyday tasks will be a struggle. Many have to hire outside help or rely on family members. Eldercare is a growing concern for many families.
AI is at a stage wherever exchange this want isn’t too far-flung, says Matthew Taylor, the man of science at Washington State University. Elderly relatives who don’t want to leave their homes could be assisted by in-home robots. That solution offers family members more flexibility in managing a loved one’s care. These robots could help seniors with everyday tasks and allow them to stay independent and living in their homes for as long as possible, improving their overall well-being.
Medical and AI researchers have even piloted systems based on infrared cameras that can detect when an elderly person falls. Researchers and medical specialists can also monitor alcohol and food consumption, fevers, restlessness, urinary frequency, chair and bed comfort, fluid intake, eating, sleeping, declining mobility, and more.
Machine learning may also be utilized in the prediction systems. Considering the loan example, to cipher the chance of a fault, the system can classify the offered information in teams. It is defined by a set of rules prescribed by the analysts. Once the classification is finished, we can calculate the probability of the fault. These computations will cipher across all the sectors for diverse functions. Making predictions is one in all the simplest machine learning applications.
We can not how content moderation is the loveliest application of machine learning. With high accessibility of the internet and modern technology, comes the bane of platform abuse too. Specifically, Pseudo-news or Fake news is the most common digital abuse at present. Outspread of disinformation via digital culture, social media, in particular, is encouraging the necessity of content moderation.
Recently, Facebook declared hiring of 3000 new employees to keep a check on the newsfeed content of the platform. In addition to this, emerging AI/ML platforms are facilitating with proprietary systems to enhance the interactions between humans and artificial intelligence to enable content moderation task.
Interestingly, these technologies address and analyze the context and content of every single frame of video using innovative tools which ultimately reduce the human involvement and divert them towards productive work.
8.Home Security and Smart Homes
Application of machine learning to home security and smart homes. For the best tech in home security, many homeowners look toward AI-integrated cameras and alarm systems. These cutting-edge systems use facial recognition software and machine learning to build a catalog of your home’s frequent visitors, allowing these systems to detect uninvited guests in an instant.
AI-powered smart homes also provide many other useful features, like tracking when you last walked the dog or notifying you when your kids come home from school. The newest systems will even need emergency services autonomously, creating it a lovely different to subscription-based services that offer similar edges.
Machine learning has a lot of potential in the financial and banking sector. It is the driving force behind the popularity of financial services. Machine learning can help banks, financial institutions to make smarter decisions. Machine learning will facilitate the money services to identify associate degree account closure before it happens. It also can track the disbursement pattern of the purchasers. Machine learning can also perform market analysis. Smart machines are often trained to trace disbursement patterns. The algorithms will determine the tends simply and might react in real-time.
10.Digital Personal Assistants
Digital Personal Assistants is one of the best application of machine learning. Imagine never needing to worry about preparing dinner, because your personal assistant knows what you like, what you have in your pantry, and which days of the week you like to cook at home. Imagine that when you get back from work, all your groceries are waiting at your doorstep, ready for you to prepare that delicious meal you’ve been craving. You even have a bonus recipe for a new dessert you’ve been meaning to try.
Digital assistants are getting smarter by the year. Companies such as Amazon and Google are pouring billions of dollars into making digital assistants even better at speech recognition and learning about our daily routines, opening the door to more and more complex tasks.
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Other than this there are many machine learning applications. We can say that machine learning is an incredible breakthrough in the field of artificial intelligence. And while machine learning has some frightening implications, these machine learning applications are one of the ways through which technology can improve our lives.