Machine Learning: Now Is The Future

Machine Learning: Now Is The Future

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In technology and much else, there’s a crucial bond between the exploration and advancement of the past and the actual occurrences of the present. Analyzing that bond is essential to the process of learning. History is an excellent mentor, particularly because, since things don’t occur in a vacuum, it’s wise to consider the present in relation to the past for most of the part.

The other most crucial bond is something of an informative query between what truly exists and what’s feasible tomorrow, which can aid to quicken the learning method. To comprehend and guide what you do today, you should also think about what you would do tomorrow.

Everything that happens around has a process, a funnel that is to be followed. In technology, this process is notably important if you’re trying to deal with problems in a way that preserves as few blind spots as achievable: if you wish to apply technology to solutions that bear hardship, you need information, context, concern — and perspective and this brings me to write about Machine Learning.

Machine Learning is one of the hottest technologies among all the technologies. It is much like how the internet came out as a game changer in everyone’s life; Artificial Intelligence and Machine Learning are balanced to revamp our lives which were unbelievable years ago.

Machine learning is a method of data analysis that automates analytical model building, focuses on the development of computer programs that can access data and use it to learn for themselves. Machine Learning is a branch of AI that focuses on the idea that systems can learn from data, identify patterns and make decisions with the slightest human interference.

Why is Machine Learning Important?

Keeping everything in mind, the increasing volumes and varieties of data available, the requirement for computational processing has become vital to provide deep-rooted information which is inexpensive and easily available. With Machine Learning, it’s possible to dehumanize models which can evaluate bigger, complex data to return faster and accurate results.

Organizations are finding beneficial opportunities to increase their business by analyzing the precise models to avoid unknown risks. Algorithms are used to build a model which is helping organizations to overpass the gap between their products and users with good decisions and least human interference. Organizations with excessive volumes of data have analyzed the importance of Machine Learning. In short, organizations can make a better decision without human intervention by using algorithms and build models that uncover connections.

How does Machine Learning work?

Machine Learning gives a machine or a software the ability to evaluate, predict and sort large amounts of data, allowing them to make data-driven decisions rather than being specifically programmed for carrying out specific tasks. This ultimately leads to less human effort. 

Who uses this technology and how has this changed our lives?

With the immense amount of data becoming more accessible today, Machine Learning is starting to move to the cloud. Data Scientists will no longer specifically custom code or manage infrastructure. ML will help the systems to scale for them, generate new models on the go and deliver faster and accurate results.

The major industries where Machine Learning is used and has made a mark are:

Healthcare

Machine learning is a life-saving technology that is transforming healthcare. It helps in predicting chronic diseases which are misdiagnosed and helps patient in giving preventive measures. Another most important contribution in the field of Machine Learning is Computer Vision. It’s one of the most active healthcare applications for ML Microsoft’s Inner Eye drive that started in 2010 and is presently working on an image diagnostic tool. Recently Google has developed a Machine Learning algorithm that helps to detect cancerous tumors and mammograms. It’s visible that Machine Learning puts another arrow in the convulsion of the healthcare industry and clinical decision making.

Digital Marketing

Machine Learning allows very good customer engagement and reaction platform. ML tools are capable of analyzing extremely large sets of data and present understandable analytics that can be useful for marketing teams. For companies using ML tools, marketing teams can get more time to specialize in other areas and use ML findings to gain new in-depth awareness to optimize their marketing strategies. ML in digital marketing helps marketers to expand their understanding of their target consumers and how they can amend their interactions with them.

Education

With enhancements in technology, Machine Learning has blessed schools and teachers with smart classes, support teachers, etc by using analytical techniques and Artificial Intelligence. It has now become an easy task to grade students fairly by removing human efforts. Machine Learning helps in the compilation of data and thus there is no need to be dependent on detailed textbooks. It has also helped a lot by determining the student’s performance by learning about each student through smart tools and thus helping them with ways to improve.

Search Engine Result Refining

Yahoo, Google, and other search engines use Machine Learning to improve the search results for us. Every time we use a search, the backend algorithms keep a record of how we respond to the search results. For example, if we stay at the second option for long the web server captures the activity and then responds the same way for the next search results. This has made searching convenient and easy. We only get the information we require.

Google Translation

Google’s Neural Machine Translation works on the endless number of languages and dictionaries by using Natural Language Processing and helps us by providing the most accurate translation of the desired sentence. This is one of the most used applications of Machine and Deep learning by making our lives easy.

Fraud Detection

Machine learning is proving its capability to make cyberspace a safe place and tracking banking related frauds online is one of its examples. For example, Citibank’s collaboration with Portugal based fraud detection company Feedzai that works in real-time to analyze and remove online fraud and in-person banking by creating alerts for the customer. PayPal too uses some set of Machine Learning tools which help them in comparing and tracking millions of transactions and differentiate between illegal and legal transactions.

Video Surveillance

Be it a shopping mall, working space or a traffic signal, cameras are present everywhere. Now imagine a single person monitoring these multiple cameras at a particular place, isn’t it a very difficult and boring job? This is why computers are trained and programmed to do such tasks. Video surveillance these days are powered by Machine Learning and Artificial Intelligence technologies helping us in crime detection before it happens. It tracks the unusual activities of people standing motionless at a place, scrolling around a park daily or any other weird activities and give alerts to humans. This helps to avoid mishaps or criminal activities.

Machine Learning in Travelling

All of us use GPS navigation services and are aware of it. When we do that our exact location, traffic variance, etc are saved at a database. This data is then used to create the current traffic map. This helps in preventing traffic and excess traffic analysis. The only problem that occurs is, not all vehicles are GPS enabled. In this scenario when GPS navigation is not available, machine Learning helps by providing estimated details using the past stored data. This has been very useful to people as this saves time.

We now know how Machine Learning has been a constant support to humans. Machine Learning can be a competing asset for any organization, be it a developed MNC or startups. Tasks which humans used to perform are now assisted by smart machines which have reduced the human effort and time. A quote by Thomas H. Davenport an American Academic and the author sums this article very well. “Humans can typically create one or two good models a week; machine learning can create thousands of models a week.”

Machine Learning has been an incredible breakthrough in every field and would stay with us in the future. You can also excel in this technology by learning through various Machine Learning Courses available online.